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20211229 homework

2021-12-29T09:06:22Z

Wei Yiwen: /* 卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526 */

20211215 homework

2021-12-29T08:59:33Z

Wei Yiwen: /* 卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526 */

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==陈静 Chén Jìng 国别女 202020080595==

鼎：古代食器。胡羼(chàn忏) ──胡闹。羼：本义为群羊杂居。引申为杂乱不纯，乱七八糟。

Tripod (Ding in Chinese): ancient food utensil. Hu Chan in Chinese means nonsense. Chan in Chinese originally means that the sheep live together, whose extensive meaning is mess.
----

Tripod: ancient food utensil. Hi Chan - nonsense. The original meaning is that sheep live together. It is extended meaning to be messy, impure and messy.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 01:25, 12 December 2021 (UTC)

==蔡珠凤 Cài Zhūfèng 法语语言文学女 202120081477==

抓──即“抓周”，亦称“试儿”、“试周”。旧俗于婴儿满周岁时，父母摆列各种小件器物，任其抓取，以测试其秉性、智愚、志趣。此俗始于江南，后亦传到北方。

Grasping -- namely "grasping the week", also known as "trying the child" and "trying the week". The old custom is that when a baby reaches the age of one year, his parents arrange all kinds of small objects and let him grab them to test his temperament, intelligence and interest. This custom began in the south of the Yangtze River and later spread to the north.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 01:23, 12 December 2021 (UTC)

Catch ─ ─ means "catch the week", also known as "test" and "test week". The old custom is when the baby reaches one year old, the parents arrange all kinds of small utensils and let them grab them to test their disposition, wisdom and ambition. This custom began in the south of the Yangtze River and then spread to the north.--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 07:41, 11 December 2021 (UTC)

==曾俊霖 Zēng Jùnlín 国别男 202120081478==

事见北朝周·颜之推《颜氏家训·风操》：“江南风俗，儿生一期(年)，为制新衣，盥浴装饰，男则用弓矢纸笔，女则刀尺针缕(线)，并加饮食之物及珍宝服玩，置之儿前，观其发意所取，以验贪亷智愚，名之为试儿。”

It is said in Yan's family instructions and customs by Yan Zhitui of the Northern Dynasty that "the custom in the south of the Yangtze River was born in the first year. It was to make new clothes and decorate bathrooms. Men used bows and arrows, paper and pens, women used knives, rulers, needles and threads (lines), and played with food and precious clothes. They were placed in front of their children and looked at what they wanted to take to test their greed, wisdom and stupidity. They were called test children."--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 07:37, 11 December 2021 (UTC)

It is said in Yan's family instructions and customs by Yan Zhitui of ''the Northern Dynasty'' that the custom in the south of the Yangtze River was born in the first year. It was to make new clothes and decorate bathrooms. Men used bows and arrows, paper and pens, women used knives, rulers, needles and threads (lines), and played with food and precious clothes. They were placed in front of their children and looked at what they wanted to take to test their greed, wisdom and stupidity. They were called test children."--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 12:20, 20 December 2021 (UTC)Chen Huini

==陈惠妮 Chén Huìnī 英语语言文学（英美文学）女 202120081479==

(宋·赵彦卫《云麓漫钞》卷二也有相同记载)又宋·叶真《爱日斋丛钞》卷一：“《玉壶野史》记曹武惠王(曹彬)始生周晬日，父母以百玩之具罗于席，观其所取。

(Song · Zhao Yanwei's ''Yunlu Manchao'', Volume 2 has the same record) and Song · Ye Zhen, Volume 1, ''Ai Ri Zhai Cong Chao'': "''In the History of Jade Pot'', when King Cao Wu hui (Cao Bin) was on the year ahead in the first week of his birth, his parents viewed the year he took with a hundred toys on the table.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 12:24, 20 December 2021 (UTC)Chen Huini

（also recorded in Volume 2 of ''Yunlu Essay'' by Zhao Yanwei，Song Dynasty） Volume 1 of ''Ai Rizhai Essay'' by Ye Zhen，Song Dynasty：“ ''History of Jade Pot'' records that King Wuhui（Cao Bin）'s parents put many toys on the table and observed his choice when he was 100 days years old.”--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:53, 22 December 2021 (UTC)

== Headline text ==
==陈湘琼 Chén Xiāngqióng 外国语言学及应用语言学女 202120081480==

武惠王左手提干戈，右手提俎豆，斯须取一印，馀无所视。曹，真定人。江南遗俗乃在此(指真定)，今俗谓试周是也。”

Lord Wuhui holds weapons with his left hand and dinnerware in his right hand.Then he looks at a seal and graps it without seeing anything else.Lord Wuhui, whose first name is Cao, comes from Zhen Ding county. The place is called Shi Zhou now, on whiche Jiang Nan's old cities lay.--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:23, 14 December 2021 (UTC)

Lord Wuhui holds weapons with his left hand and dinnerware in his right hand.Then he looks at a seal and graps it without seeing anything else.Lord Wuhui, whose first name is Cao, comes from Zhen Ding county. The place is so-called Shizhou now, on which ancient Jiangnan lay.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:07, 14 December 2021 (UTC)

==陈心怡 Chén Xīnyí 翻译学女 202120081481==

致知格物──语出《礼记·大学》：“致知在格物，格物而后知至。”意谓要想获得知识，必须探究事物的道理。致：获得，取得。

Zhi Zhi Ge Wu- ''From The Book of Rites·Daxue'': "Zhizhi lies in Gewu, and after Gewu, knowledge arrives." It means that in order to gain knowledge, one must inquire into the truth of things. Zhi: To acquire, to obtain.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:18, 12 December 2021 (UTC)

Zhi Zhi Ge Wu - originated from ''The Book of Rites·Daxue'': "The intention of Zhizhi refers to Gewu, and after the process of Gewu, knowledge will be obtained." It means that in order to gain knowledge, one must inquire into the truth of things. Zhi: to acquire, and to obtain.--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 14:45, 20 December 2021 (UTC)

==程杨 Chéng Yáng 英语语言文学（英美文学）女 202120081482==

格：推究，探究，探讨。尧……张──尧、舜、禹、汤、文、武，即唐尧、虞舜、夏禹、成汤、周文王、周武王，是从上古至西周的明君；
Ge: means deduction, exploration and discussion. Yao...Zhang──Yao, Shun, Yu, Tang, Wen, Wu, namely Tang Yao, Yu Shun, Xia Yu, Cheng Tang, Emperor Wen of Zhou Dynasty, Emperor Wu of Zhou Dynasty, they are all wise emperors from ancient times to the Zhou Dynasty;--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 13:11, 11 December 2021 (UTC)

Ge: means deduction, exploration and discussion. Yao...Zhang──Yao, Shun, Yu, Tang, Wen, Wu, namely Tang Yao, Yu Shun, Xia Yu, Cheng Tang, Emperor Wen of Zhou Dynasty, Emperor Wu of Zhou Dynasty, they are all wise emperors from ancient times to Zhou Dynasty;--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 12:13, 19 December 2021 (UTC)

==丁旋 Dīng Xuán 英语语言文学（英美文学）女 202120081483==

周、召，即周公旦、召公奭，都是西周的贤相；孔、孟，即孔丘(通称孔子)、孟轲(通称孟子)，都是儒学的创始人；董、韩、周、程、朱、张，即汉代董仲舒、唐代韩愈、北宋周敦颐、北宋程颢和程颐兄弟、南宋朱熹、北宋张载，都是儒学理论家。

Zhou, called the Duke of Zhou, and Zhao, called Duke of Shi, are both talented prime ministers (in feudal China); Kong (generally called Confucius) and Meng (generally called Mencius) are both founders of Confucianism; Dong (Dong Zhongshu in Han Dynasty), Han (Han Yu in Tang Dynasty), Zhou (Zhou Dunyi in the Northern Song Dynasty), Cheng (Cheng Jing and Cheng Yi brothers in the Northern Song Dynasty), Zhu (Zhu Xi in the Southern Song Dynasty), Zhang (Zhang Zai in the Northern Song Dynasty) are all Confucian theorists. --[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 07:19, 12 December 2021 (UTC)

Zhou and Zhao are respectively the Duke of Zhou and the Duke of Shi and both are talented prime ministers of the Western Zhou Dynasty; both Kong (generally called Confucius) and Meng (generally called Mencius) are founders of Confucianism; Dong (Dong Zhongshu in Han Dynasty), Han (Han Yu in Tang Dynasty), Zhou (Zhou Dunyi in the Northern Song Dynasty), Cheng (Cheng Jing and Cheng Yi brothers in the Northern Song Dynasty), Zhu (Zhu Xi in the Southern Song Dynasty), Zhang (Zhang Zai in the Northern Song Dynasty) are all Confucian theorists. --[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 08:09, 12 December 2021 (UTC)

==杜莉娜 Dù Lìnuó 英语语言文学（语言学）女 202120081484==

这些人皆是儒家竭力推崇的人物。蚩尤……秦桧──蚩尤、共工，都是传说中上古最凶恶的部族首领；桀、纣、始皇，即夏桀、商纣王、秦始皇，都是登峰造极的暴君；

All these people are strong recommended by confucianists such as Chi You(a mythological warrior engaged in fighting with the Yellow Emperor), Qin Hui (a traitor in the Song dynasty in Chinese history)and so on. Among them both Chi You and Gong Gong (the water god in ancient Chinses history and the devil of floods) are the most ferocious tribal chief in the Chinese legend;and all Xia Jie, Shang Zhou and Qin Shi Huang, being respectively the emperor Jie of Xia Dynasty，the emperor Zhou of Shang Dynasty and the first emperor of Qin Dynasty, are extremely tyrannical.

All these people are strongly recommended by Confucianists such as Chi You(a mythological warrior engaged in fighting with the Yellow Emperor), Qin Hui (a traitor in the Song dynasty in Chinese history)and so on. Among them both Chi You and Gong Gong (the water god in ancient Chinses history and the devil of floods) are the most ferocious tribal chief in the Chinese legend;and all Xia Jie, Shang Zhou and Qin Shi Huang, being respectively the emperor Jie of Xia Dynasty，the emperor Zhou of Shang Dynasty and the first emperor of Qin Dynasty, are extremely tyrannical.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 14:13, 19 December 2021 (UTC)

==付红岩 Fù Hóngyán 英语语言文学（英美文学）女 202120081485==

王莽、曹操、桓温、安禄山、秦桧，他们分别是汉代、三国、东晋、唐代、南宋人，都是大奸臣乃至叛逆之贼。许由……朝云──许由，传说他是上古时为了逃避帝位而终生隐居的贤人；陶潜(即陶渊明)、阮籍、嵇康、刘伶，都是魏晋时期著名文学家及不与流俗同低昂的独行之士；

Wang Mang, Cao Cao, Huan Wen, An Lushan and Qin Kuei, who were in the Han Dynasty, the Three Kingdoms, the Eastern Jin Dynasty, the Tang Dynasty and the Southern Song Dynasty respectively, were all great treacherous court officials and even traitors. It were Xu You... Zhao Yun -- Xu You who were said a sage who lived in seclusion all his life in order to escape the throne in ancient times. Tao Qian (Tao Yuanming), Ruan Ji, Ji Kang and Liu Ling were all prestigious persons in the Wei and Jin dynasties and mavericks who did not flow along with the turbid currents of the mainstream thought.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 14:10, 19 December 2021 (UTC)

Wang Mang, Cao Cao, Huan Wen, An Lushan and Qin Kuei, who were in the Han Dynasty, the Three Kingdoms, the Eastern Jin Dynasty, the Tang Dynasty and the Southern Song Dynasty respectively, were all great treacherous court officials and even traitors. Xu You... Zhao Yun -- Xu You. It is said that he was a sage who lived in seclusion all his life in order to escape the throne in ancient times. Tao Qian (Tao Yuanming), Ruan Ji, Ji Kang and Liu Ling were all famous writers in the Wei and Jin dynasties and mavericks who did not flow along with the turbid currents of the world.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 11:57, 19 December 2021 (UTC)

==付诗雨 Fù Shīyǔ 日语语言文学女 202120081486==

王谢二族，指东晋王导和谢安，都是显贵；顾虎头，即顾恺之，字虎头，是东晋名画家；陈后主、唐明皇、宋徽宗，都是有才气的风流皇帝；

The Two families of Wang and Xie, namely Wang Dao and Xie An, were both nobility in the Eastern Jin Dynasty. Gu Hutou, also known as Gu Kaizhi, was a famous painter in the Eastern Jin Dynasty. Emperor Chen Shubao of Chen, Emperor Ming of Tang and Emperor Huizong of Song were all talented and romantic emperors.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 10:07, 12 December 2021 (UTC)

The Two families of Wang and Xie, namely Wang Dao and Xie An, were both of the nobility in the Eastern Jin Dynasty. Gu Hutou, also known as Gu Kaizhi, was a famous painter in the Eastern Jin Dynasty. Emperor Chen Shubao of Chen, Emperor Ming of Tang and Emperor Huizong of Song were all talented and romantic emperors. --[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 01:02, 13 December 2021 (UTC)

==高蜜 Gāo Mì 翻译学女 202120081487==

刘庭芝即刘希夷(字庭芝)、温飞卿即温庭筠(字飞卿)，都是唐代名诗人；米南宫即米芾(南宫为世称)，是北宋名画家；石曼卿即石延年(字曼卿)、柳蓍卿即柳永(字蓍卿)、秦少游即秦观(字少游)，都是北宋著名文学家；

Liu Tingzhi, or Liu Xiyi (courtesy name Tingzhi), Wen Feiqin refers orWen Tingyun (courtesy name Feiqing) are both famous poets of the Tang Dynasty. Mi Nangong, or Mi Fu (nickname Nangong), was a famous painter of the Northern Song Dynasty; Shi Manqing, or Shi Yannian (courtesy name Manqing), Liu Yaoqing, or Liu Yong (courtesy name Yaoqing), and Qin Shaoyou, or Qin Guan (courtesy name Shaoyou), were famous literary scholars of the Northern Song Dynasty.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 01:03, 13 December 2021 (UTC)

Liu Tingzhi, or Liu Xiyi (styled Tingzhi), Wen Feiqin refers orWen Tingyun (styled Feiqing) are both famous poets of the Tang Dynasty. Mi Nangong, or Mi Fu (nickname Nangong), was a famous painter of the Northern Song Dynasty; Shi Manqing, or Shi Yannian (styled Manqing), Liu Yaoqing, or Liu Yong (styled Yaoqing), and Qin Shaoyou, or Qin Guan (styled Shaoyou), were famous literary scholars of the Northern Song Dynasty.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 12:27, 15 December 2021 (UTC)

==宫博雅 Gōng Bóyǎ 俄语语言文学女 202120081488==

倪云林即倪瓒，字云林，是元代名画家；唐伯虎即唐寅(字伯虎)、祝枝山即祝允明(字枝山)，都是明代名画家、文学家；李龟年(唐代人)、黄幡绰(唐代人)、敬新磨(五代后唐人)，都是名艺人；

Ni Yunlin, i.e Ni Zan, was a famous painter in the Yuan Dynasty. Tang Bohu i.e Tang Yin (styled Bohu), Zhu Zhishan i.e Zhu Yunming (styled Zhishan), are famous Ming dynasty painters, litterateurs; Li Gunian (Tang Dynasty), Huang Fan Chuo (Tang Dynasty), Jing Xinmo (five dynasties later Tang dynasty), are famous artists;--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 12:23, 15 December 2021 (UTC)

Ni Yunlin, or Ni Zan, or Ni Yunlin, was a famous painter in the Yuan dynasty; Tang Bohu (or Tang Yin) and Zhu Zhishan (or Zhu Yunming) were famous painters and literary figures in the Ming dynasty; Li Guinian (of the Tang dynasty), Huang Fanchuo (of the Tang dynasty), and Jing Xinmo (of the post-Tang dynasty of the Five Dynasties) were all famous artists.--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 06:39, 15 December 2021 (UTC)

==何芩 Hé Qín 翻译学女 202120081489==

卓文君(已见第一回注)、红拂(先为隋相杨素的侍女，后私奔李靖，也是前蜀·杜光庭《虬髯客传》中的女主人公)、薛涛(唐代才妓)、崔莺(即唐·元稹《会真记》、元·王实甫《西厢记》中的崔莺莺)、朝云(宋代名妓)，他们都是以才貌流芳的名女。

Zhuo Wenjun (see the first chapter note), Hong Fu (she used to be as the servant of the Sui minister Yang Su, then eloping to Li Jing; she was also the heroine of ''The Legend of the Gnarled Man'' by Du Guangting), Xue Tao (a talented prostitute of the Tang Dynasty), Cui Ying (i.e. Cui Yingying of Yuan Zhen's ''The Book of Hui Zhen'' and Wang Shifu's "The Western Chamber"), Zhaoyun (a famous prostitute of the Song Dynasty), they are all famous for their talent and beauty. --[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 06:32, 15 December 2021 (UTC)

Zhuo Wenjun ( the first chapter noted), Hong Fu (she used to be as the servant of the minister of Sui Dynasty Yang Su, then eloping to Li Jing, also the heroine of ''The Legend of the Gnarled Man'' by Du Guangting), Xue Tao (a talented prostitute of the Tang Dynasty), Cui Ying (namely Cui Yingying of Yuan Zhen's ''The Book of Hui Zhen'' and Wang Shifu's "The Western Chamber"), Zhaoyun (a famous prostitute of the Song Dynasty), they are all famous for their talent and beauty.--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 12:25, 19 December 2021 (UTC)

==胡舒情 Hú Shūqíng 英语语言文学（语言学）女 202120081490==

成则公侯败则贼──意谓成功的人便能获得公爵、侯爵之类的高官显爵，失败的人便被看作贼寇。表示世上并无公理，世人不讲是非，只论成功与失败，即只以成败论英雄。这里化用了“败则盗贼，成则帝王”。

Success makes the Duke while failure makes the theif ——which means that, If one is successful, he will be worshipped as the Duke. While one is unsuccessful, he will be despised as the thief. It expresses that there is no generally acknowledged truth in the world and people neglect justice and only pay attention to success and failure, that is, the sole measure. It coins a phrase here, “Failure makes a thief， success a king.”--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 12:25, 19 December 2021 (UTC)

The winner is Duke, the looser is theif means that the person who succeeded would be entitled like Duke and who failed would be dispised as a theif. It presents that there is no generally acknowledged truth in the world and people neglect justice and only pay attention to success and failure, that is, the sole measure. It coins a phrase here, “Failure makes a thief， success a king.”--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 14:58, 12 December 2021 (UTC)

==黄锦云 Huáng Jǐnyún 英语语言文学（语言学）女 202120081491==

出自宋·邓牧《君道》：“嘻！天下何常之有？败则盗贼，成则帝王。”东床──指女婿。典出《晋书·王羲之传》、南朝宋·刘义庆《世说新语·雅量》：晋朝太尉郗鉴派人至丞相王导家相婿，王丞相令其到东厢房随意挑选。

It is cited from Deng Mu's How to Be Emperor, a work in Song dynasty, saying "how can the world be immutable! The loser is the thief, and the winner is the emperor." Dongchuang refers to the son-in-law, used in Books of Jin: Wang Xizhi's Biography" and Liu Yiqing's "Shi Shuo Xin Yu · Elegance" (Southern Song dynasty): In Jin dynasty Tai Wei (supreme government official in charge of military affairs) Xijian sent an underlying to the prime minister Wang Dao's house for taking in a son-in-law, and Prime Minister Wang invite him to choose at will in the east wing.--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 14:43, 12 December 2021 (UTC)

It is cited from Deng Mu's How to Be Emperor, a work in Song dynasty, saying "how can the world be immutable! The loser is the thief, and the winner is the emperor." Dongchuang refers to the son-in-law, used in Books of Jin: Wang Xizhi's Biography" and Liu Yiqing's "Shi Shuo Xin Yu · Elegance" (Southern Song dynasty): In Jin dynasty Tai Wei (supreme government official in charge of military affairs) Xijian sent an official to the prime minister Wang Dao's house choosing a son-in-law, and Prime Minister Wang invited him to choose at will in the east wing room.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 14:51, 12 December 2021 (UTC)

==黄逸妍 Huáng Yìyán 外国语言学及应用语言学女 202120081492==

此人过去一看，见王家诸郎皆很矜持，唯独王羲之坦腹躺在东床之上，毫不在乎。此人回报，郗鉴即选中王羲之为婿。后世即以“东床”、“东床坦腹”、“东床客”、“东床娇客”等代指女婿。

The man looked over and saw that all the lords of Wang family were very reserved, except Wang Xizhi, who was lying on the east bed and didn't care, showing his belly. In return, Xi Jian chose Wang Xizhi as his son-in-law. Later generations referred to the son-in-law with "East Bed", "East Bed Man Showing Belly", "East Bed Guest", "East Bed Distinguished Guest" and so on.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 04:59, 12 December 2021 (UTC)

The man looked over and saw that all the lords of Wang family were very reserved, except Wang Xizhi, who was lying on the east bed and didn't care, showing his belly. In return, Xi Jian chose Wang Xizhi as his son-in-law. Later generations referred to the son-in-law with "East Bed", "East Bed Man Showing Belly", "East Bed Guest", "East Bed Distinguished Guest" and so on.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:54, 19 December 2021 (UTC)Huang Zhuliang

==黄柱梁 Huáng Zhùliáng 国别男 202120081493==

退了一舍之地──意谓退避三十里。形容退居其后，不敢与争。一舍：三十里。这里化用了“退避三舍”之典。He retreat thirty miles. It describes retreating behind and not daring to compete with. Yishe: Thirty Li. The code of "retreat and give up" is used here.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:53, 19 December 2021 (UTC)Huang Zhuliang

He retreat thirty miles. It describes retreating behind and not daring to compete with. Yishe: Thirty Li. The code of "retreat and give up" is used here
--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 12:02, 19 December 2021 (UTC)

==金晓童 Jīn Xiǎotóng 202120081494==

典出《左传·僖公二十三年》：春秋时，晋国公子重耳出奔至楚，楚成王礼遇之，因问道：“公子若反(返)晋国，则何以报不谷？”重耳对曰：“若以君之灵，得反晋国，晋、楚治兵，遇于中原，其辟(避)君三舍。”
This story comes from ''Zuo Zhuan · Xi public twenty three years'': During the Spring and Autumn Period (777-476 BC), Childe Chong Er of the state of Jin went to the state of Chu. King Cheng of Chu gave a banquet for Chong er and asked, "If childe returns to the state of Jin, how will you repay me? Chong Er answered, "If I can return to the state of Jin, if the troops of the state of Jin and the state of Chu meet each other in the Central Plains, I will ask the troops of the state of Jin to retreat 90 li.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 06:56, 12 December 2021 (UTC)

==邝艳丽 Kuàng Yànl 英语语言文学（语言学）女 202120081495==

后重耳返国为君，晋、楚城濮(在今山东省鄄城县西南)之战，重耳遵守诺言，晋军果“退三舍以辟之”。

第三回

托内兄如海荐西宾接外孙贾母惜孤女

Then Childe Chong Er came back to his country as Emperor. In the battle of Jin and Chu in Chengpu (in southwest of Juancheng county in Shandong province), he keeps his promise, then the army of Jin actually retreated to avoid the war.

Chapter 3

Entrust cousin Ru Hai with recommendations of distinguished gusts; Accept granddaughter lady Dowager takes pity on orphan girl

Then Childe Chong Er came back to his country as Emperor. In the battle of Jin and Chu in Chengpu (in southwest of Juancheng county in Shandong province), he keeps his promise, then the army of Jin actually retreated to avoid the war.

Chapter 3

Entrust cousin Ru Hai with recommendations of distinguished gusts; Welcoming her granddaughter, lady Dowager takes pity on the orphan girl.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 11:13, 20 December 2021 (UTC)

==李爱璇 Lǐ Àixuán 英语语言文学（语言学）女 202120081496==

却说雨村忙回头看时，不是别人，乃是当日同僚一案参革的张如圭。他系此地人，革后家居，今打听得都中奏准起复旧员之信，他便四下里寻情找门路，忽遇见雨村，故忙道喜。二人见了礼，张如圭便将此信告知雨村。

Yue-ts'un, turning round in a hurry, perceived that the speaker was no other than a certain Chang Ju-kuei, an old colleague of his, who had been denounced and deprived of office, on account of some case or other; a native of that district, who had, since his degradation, resided in his home.Having come to hear the news that a memorial, presented in the capital, that the former officers (who had been cashiered) should be reinstated, had received the imperial consent, he had promptly done all he could, in every nook and corner, to obtain influence, and to find the means (of righting his position,) when he, unexpectedly, came across Yue-ts'un, to whom he therefore lost no time in offering his congratulations. The two friends exchanged the conventional salutations, and Chang Ju-kuei communicated the tidings to Yue-ts'un.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 07:11, 25 December 2021 (UTC)

Yue-ts'un, speedily looking back on, perceived that the speaker was no other than a certain Chang Ju-kuei, an old colleague of his, who had participated in the former case but been denounced and deprived of office, on account of some case or other. He was a native of that district, who had resided at home since his degradation. Having lately come to hear the news that a memorial, presented in the capital, that the former officers (who had been cashiered) should be reinstated, had received the imperial consent, he had promptly done all he could to obtain influence, and to find the means of righting his position. When he, unexpectedly, came across Yue-ts'un, he offered offering his congratulations to him soon. The two friends greeted to each other, exchanging the conventional salutations, and Chang Ju-kuei forthwith passed on the information to Yue-ts'un.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 04:55, 15 December 2021 (UTC)

==李瑞洋 Lǐ Ruìyáng 英语语言文学（英美文学）女 202120081497==

雨村欢喜，忙忙叙了两句，各自别去回家。冷子兴听得此言，便忙献计，令雨村央求林如海，转向都中去央烦贾政。雨村领其意而别，回至馆中，忙寻邸报看真确了。次日，面谋之如海。如海道：“天缘凑巧。

Yue-ts'un was delighted, but after he had made a few remarks in a hurry, each took his leave and sped on his own way homewards. After hearing this conversation, Leng Tzu-hsing hastened at once to propose a plan, advising Yue-ts'un to request Lin Ju-hai, then, in his turn, to appeal to Chia Cheng in the capital for support. Yue-ts'un accepted the suggestion, and took leave of him. Upon returning to the quarter, he made all haste to lay his hand on the Metropolitan Gazette, to ascertain whether the news was authentic or not. On the next day, he had a personal consultation with Ju-hai. "Providence and good fortune are both alike propitious!" said by Ju-hai.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 04:57, 15 December 2021 (UTC)

Yue-ts'un was delighted, but after he they made a short conversation, each of them stepped on their own way homewards. After hearing the words of Yue-ts'un, Leng Tzu-hsing hastened at once to propose a plan, advising Yue-ts'un to request Lin Ju-hai, then, in his turn, to appeal to Chia Cheng in the capital for support. Yue-ts'un accepted the suggestion, and took leave of him. Upon returning to the quarter, he made all haste to read the Metropolitan Gazette, to ascertain the authenticity of that news. On the next day, he made a personal consultation with Ju-hai. Thus, Ju-hai said, "Providence and good fortune are both alike propitious!" --[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 13:06, 15 December 2021 (UTC)

==李姗 Lǐ Shān 英语语言文学（英美文学）女 202120081498==

因贱荆去世，都中家岳母念及小女无人依傍，前已遣了男女、船只来接，因小女未曾大痊，故尚未行。此刻正思送女进京。因向蒙教训之恩，未经酬报，遇此机会，岂有不尽心图报之理？弟已预筹之，修下荐书一封，托内兄务为周全，方可稍尽弟之鄙诚；

Since my wife has passed away, my mother-in-law has long before dispatched servants and transporting boats here to fetch my lonely daughter. But she has not set off yet due to the fact that she had not fully recovered at that time. As she is in good condition now, I am considering sending her to her grandma's. Once you have taught my daughter but desired no handsome payment; while now you need help, how can I sit on the fence? I have already well prepared for that in advance --- a recommendation letter has been written to my brother-in-law, to ensure your success in career. Only in this way can I show my gratitude towards you.--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 08:15, 11 December 2021 (UTC)

Since my wife has passed away, my mother-in-law who lives in the capital worried that my daughter has no one to rely on. So she has long before dispatched servants and transporting boats here to fetch my lonely daughter. But she has not set off yet due to the fact that she had not fully recovered at that time. As she is in good condition now, I am considering sending her to her grandma's. Once you have taught my daughter but desired no handsome payment; while now you need help, how can I sit on the fence? I have already well prepared for that in advance --- a recommendation letter has been written to my brother-in-law, to ensure your success in career. Only in this way can I show my gratitude towards you.--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 07:43, 12 December 2021 (UTC)

==李双 Lǐ Shuāng 翻译学女 202120081499==

即有所费，弟于内家信中写明，不劳吾兄多虑。”雨村一面打恭，谢不释口；一面又问：“不知令亲大人现居何职？只怕晚生草率，不敢进谒。”如海笑道：“若论舍亲，与尊兄犹系一家，乃荣公之孙：大内兄现袭一等将军之职，名赦，字恩侯；

“As for the possible costs, I will explain in the letter. You don’t need to worry about it.” Yu Cun bent down and expressed his gratitude, asking: “What does your brother do now? I’m worried that I would take the liberty to pay a visit, it’s too hasty.” Ru Hai laughed and said: “My brother and your brother belong to the same family. They are both descendants of Origin Merchant. My eldest brother is now a first-class general, his name is Pardon Merchant, whose alternative given name is Enhou.”--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 07:38, 12 December 2021 (UTC)

“As for the possible costs, I will explain in the letter. You needn’t to worry about it.” Yu Cun bent down and expressed his gratitude, asking: “What does your brother do now? I’m worried that I would take the liberty to pay a visit, it’s too hasty.” Ru Hai laughed and said: “My brother and your brother belong to the same family. They are both descendants of Ronggong. The eldest brother of my wife is now a first-class general, his name is Pardon Merchant, whose alternative given name is Enhou.” --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 23:46, 12 December 2021 (UTC)

==李文璇 Lǐ Wénxuán 英语语言文学（英美文学）女 202120081500==

二内兄名政，字存周，现任工部员外郎，其为人谦恭厚道，大有祖父遗风，非膏粱轻薄之流，故弟致书烦托，否则不但有污尊兄清操，即弟亦不屑为矣。”雨村听了，心下方信了昨日子兴之言，于是又谢了林如海。

“The second brother of my wife named Zheng, his style name is Cunzhou. He is the Yuanwai official of the Ministry of Works in feudal China. He is moderate and kind, has the dignity of his grandfather, and is not the flimsy type. Therefore, my brother sent a letter to me. Otherwise, I will not only pollute my brother's operation, but also despise my brother.” After hearing this, Yuchun had believed the words of Zixing yesterday, therefore, he thanked Lin Ruhai again. --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 01:27, 12 December 2021 (UTC)

The second brother-in-law is named Zheng, and the word is kept in Zhou. He is currently a member of the Ministry of Engineering. He is courteous and kind. He has a grandfather's legacy. He is not anointing and frivolous. Disdainful. "Yucun listened, and believed in Xing's words from yesterday, so he thanked Lin Ruhai again.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 14:12, 12 December 2021 (UTC)

==李雯 Lǐ Wén 英语语言文学（英美文学）女 202120081501==

如海又说：“择了出月初二日小女入都，吾兄即同路而往，岂不两便？”雨村唯唯听命，心中十分得意。如海遂打点礼物并饯行之事，雨村一一领了。那女学生原不忍离亲而去，无奈他外祖母必欲其往，且兼如海说：“汝父年已半百，再无续室之意；
Ruhai also said: "I chose the girl to enter the capital on the second day of the lunar month, and my brother will go the same way. Isn't it both convenient?" Yucun obeyed,and RuHai was very satisfied . Ruhai then took some gifts and walked away, and Yucun took them one by one. The girl student couldn't bear to leave her relatives, but his grandmother wanted to go there. She also said like the sea: "Your father is half a hundred years old, and there is no intention to remarry.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 14:11, 12 December 2021 (UTC)
Ruhai said, "I chose the second day of the month to enter the capital, and my brother went the same way. Rain village obedient, the heart is very proud. Such as Haisui make gifts and farewell dinner, Rain village one by one. The girl could not bear to leave her, but her grandmother wanted her to go, saying, "Your father is fifty years old, and has no intention of staying in the house;--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 12:27, 19 December 2021 (UTC)

==李新星 Lǐ Xīnxīng 亚非语言文学女 202120081503==

且汝多病，年又极小，上无亲母教养，下无姊妹扶持。今去依傍外祖母及舅氏姊妹，正好减我内顾之忧，如何不去？”黛玉听了，方洒泪拜别，随了奶娘及荣府中几个老妇登舟而去。雨村另有船只，带了两个小童，依附黛玉而行。
You are sick, you are young, you have no mother to nurse you, and no sisters to nurse you. Now I am going to my grandmother and my uncle and sisters, which will relieve my worries. Why not?" When Daiyu heard this, she said goodbye with tears and followed the wet nurse and some old women in the Rong House to the boat. Yucun had another boat with two children attached to Daiyu.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 12:25, 19 December 2021 (UTC)

And you are sick, very young, no mother to raise, no sister support. Today I go to rely on my grandmother and uncle's sisters, just to reduce my internal worries, how not to go? Dai Yu listened, and Fang shed tears to say goodbye, and followed the grandmother and several old women in the Rong Mansion to board the boat. There was another boat in the rain village, with two children, who were attached to Daiyu.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 12:29, 19 December 2021 (UTC)

==李怡 Lǐ Yí 法语语言文学女 202120081504==

一日到了京都，雨村先整了衣冠，带着童仆，拿了宗侄的名帖，至荣府门上投了。彼时贾政已看了妹丈之书，即忙请入相会。见雨村相貌魁伟，言谈不俗；且这贾政最喜的是读书人，礼贤下士，拯溺救危，大有祖风；况又系妹丈致意：因此优待雨村，更又不同。
One day, when YuCun arrived in Jingdou, he dressed himself, and went to Rongfu with his nephew's name card. At this time Master Jia had seen his brother-in-law's letter, immediately invited him to come in to meet. Yucun looked tall and handsome and talked well. And Master Jia most like scholar, courtesy, saving, great predecessors style; Therefore, Master Jia is very good to Yucun. He is different from others.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 08:18, 11 December 2021 (UTC)

One day, when YuCun arrived in Jingdou, he dressed himself, and went to Rongfu with his nephew's name card. At the very moment that Master Jia had received his brother-in-law's letter, he immediately invited him to come in to meet. Yucun looked tall and handsome and talked well. And Master Jia most like scholar, courtesy, saving, great predecessors style; Therefore, Master Jia is very good to Yucun. He is different from others--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 12:39, 19 December 2021 (UTC)

==刘沛婷 Liú Pèitíng 英语语言文学（英美文学）女 202120081505==

便极力帮助，题奏之日，谋了一个复职。不上两月，便选了金陵应天府，辞了贾政，择日到任去了，不在话下。且说黛玉自那日弃舟登岸时，便有荣府打发轿子并拉行李车辆伺候。这黛玉尝听得母亲说，他外祖母家与别人家不同

They tried to help, the day of the title, sought a reinstatement. Within two months, he was elected to Jinling Yingtianfu, resigned from Jia Zheng, and left for his post on a certain day. Now, when Daiyu abandoned her boat and landed on the shore that day, she was served by a sedan chair sent by the Rongfu and a luggage cart. Daiyu heard from her mother that her grandmother's family was different from others.--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 12:40, 19 December 2021 (UTC)

They sought to a position the day that he presented a petition to the throne. Within two months, he was elected to Jinling Mansion, resigned from Master Merchant，and left for his post on a certain day. Now, when Daiyu disembarked that day, she was served by a sedan chair sent by the Rongguo Mansion and a luggage cart. Daiyu heard from her mother that her grandmother's family was different from others.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 12:44, 19 December 2021 (UTC)

==刘胜楠 Liú Shèngnán 翻译学女 202120081506==

他近日所见的这几个三等的仆妇，吃穿用度，已是不凡；何况今至其家，都要步步留心，时时在意，不要多说一句话，不可多行一步路，恐被人耻笑了去。自上了轿，进了城，从纱窗中瞧了一瞧，其街市之繁华，人烟之阜盛，自非别处可比。

In the past few days, she has been deeply impressed by the food, clothing and behavior of the low- ranking attendants who accompanied her. She decided that in their new home, she must always be vigilant and carefully weigh every word so as not to be ridiculed for any stupid mistake. When she carried into the city, she peeped out through the gauze window on her chair at the bustling and crowded streets, which she had never seen before.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 08:32, 11 December 2021 (UTC)

The three-class servants she had seen recently have an extraordinary cost of food and clothing. What's more, since got on the sedan chair and entered the city, the prosperous market and the populousness of the city through the screen window were not comparable to other places. when coming to grandmother's mansion must pay attention to every step and be cautious with words so as not to be ridiculed by others. Daiyu thought. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 15:56, 12 December 2021 (UTC)Liu Wei

==刘薇 Liú Wēi 国别女 202120081507==

又行了半日，忽见街北蹲着两个大石狮子，三间兽头大门，门前列坐着十来个华冠丽服之人。正门不开，只东、西两角门有人出入。正门之上有一匾，匾上大书“敕造宁国府”五个大字。黛玉想道：“这是外祖的长房了。”

After half day, there are two large stone lions squatting on the north side of the street, three gates decorated with beast head, and a dozen people in gorgeous crowns and clothes are sitting in front of the gate. The main gate is closing, only the east and west corners enterences are accessible. There is a plaque above the main gate with five big characters "Ningguo Mansion". "That must be grandfather's the first son's mansion."Daiyu thought. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 15:39, 12 December 2021 (UTC)Liu Wei

After another half-day walk, they came to a street with two huge stone lions crouching on the north side and three gates decorated with beast head, in front of which ten or more people in gorgeous crowns and clothes were sitting. The main gate was shut, with only people passing in and out of the other two smaller gates. On a board above the main gate was written in big characters "Ningguo Mansion Built at Imperial Command". Daiyu realized that this must be where the elder branch of her grandmather's family lived.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 05:40, 13 December 2021 (UTC)

==刘晓 Liú Xiǎo 英语语言文学（英美文学）女 202120081508==

又往西不远，照样也是三间大门，方是荣国府，却不进正门，只由西角门而进。轿子抬着走了一箭之远，将转弯时便歇了轿，后面的婆子也都下来了。另换了四个眉目秀洁的十七八岁的小厮上来抬着轿子，众婆子步下跟随。

A little further to the west they came to another three gates. This was the Rong Mansion. Instead of going through the main gate, they entered the one on the west. The bearers carried the chair a bow-shot further, and then set it down at the turning and withdrew, the maidservants now going down the chair. Another four seventeen or eighteen smartly dressed lads picked up the chair, followed by the maids.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 05:09, 12 December 2021 (UTC)

Not far to the west is the same three-room gate, which is the Rongguo Mansion. Instead of going through the main gate, they entered the one on the west. The bearers carried the chair a bow-shot further, and then set it down at the turning and withdrew, the maidservants now going down the chair. Another four seventeen or eighteen smartly dressed lads picked up the chair, followed by the maids.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 07:26, 12 December 2021 (UTC)

==刘越 Liú Yuè 亚非语言文学女 202120081509==

至一垂花门前落下，那小厮俱肃然退出。众婆子上前打起轿帘，扶黛玉下了轿。黛玉扶着婆子的手，进了垂花门，两边是超手游廊，正中是穿堂，当地放着一个紫檀架子大理石屏风。转过屏风，小小三间厅房。

When the palanquin was dropped in front of a pendant door, the attendants all retired in silence. The ladies came forward and raised the curtain of the palanquin and helped Daiyu out of the palanquin. The two sides of the door are overhand corridors, and the centre is a hall with a marble screen on a rosewood frame. Turning past the screen, there is a small three-room hall.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 07:22, 12 December 2021 (UTC)

After the palanquin was dropped in front of a floral-pendant gates, the attendants all retreated in silence. The maids came forward and drew the curtain of the palanquin to help Mascara Jade Forest out of the palanquin. Holding the hands of those maids, Black Jade enter the floral-pendant gates. On the two sides of the door were Chaoshou veranda, and in the center was a vestibule with a marble screen in a rosewood frame. Past the screen, there were three small rooms. --[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 13:01, 19 December 2021 (UTC)

==刘运心 Liú Yùnxīn 英语语言文学（英美文学）女 202120081510==

厅后便是正房大院：正面五间上房，皆是雕梁画栋；两边穿山游廊、厢房，挂着各色鹦鹉、画眉等雀鸟。台阶上坐着几个穿红着绿的丫头，一见他们来了，都笑迎上来道：“刚才老太太还念诵呢，可巧就来了。”于是三四人争着打帘子。一面听得人说：“林姑娘来了。”

Behind the banqueting hall was the courtyard of the principal rooms: the five principal rooms on the front all had carved beams and painted rafters; from the roof of the verandah on both sides, the cages of parrots, thrushes and various birds hung there. A few girls in red and green sat on the steps. Saw they coming, the girls all smiled and came up: “Just now grandma was taking about you. You arrived just in time.” Then they rushed to pull the curtain. From the other side, a man said: “Miss Forest is coming.”--[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:28, 19 December 2021 (UTC)

Behind the hall was the courtyard of the central house: five principal rooms in the front with carved beams, while along two sides corridors and chambers with colorfully painted birds as parrots and thrush. There were several maids in red and green sitting on the steps. Seeing visitors coming, they greeted them with smiles, saying, "The old lady just talked about you again and again in anticipation, and here you are." then the four maids scrambled to open the curtain. Meanwhile a man said, "Miss Lin is coming."--[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 12:47, 19 December 2021 (UTC)

==罗安怡 Luó Ānyí 英语语言文学（英美文学）女 202120081511==

黛玉方进房，只见两个人扶着一位鬓发如银的老母迎上来。黛玉知是外祖母了，正欲下拜，早被外祖母抱住，搂入怀中，“心肝儿肉”叫着大哭起来。当下侍立之人无不下泪，黛玉也哭个不休。众人慢慢解劝，那黛玉方拜见了外祖母。
An silver-haired old lady supported by two maids came and welcomed her while Black Jade entered the room. Realizing that this was her grandmother, Black Jade was about to bow down to show her respects. Suddenly she was tightly hugged by grandmoa who crying out harrowingly "my sweet heart!" Servants and maids were all in tears, and Black Jade also sobbed unceasingly. People persuaded them softly, then Black Jade was able to pay her respects to her grandmother. --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 12:14, 19 December 2021 (U

As Dai Yu just came to the home, there came a silver-haired old woman.Dai Yu knew she was grandma, and as she was going to bow down to show her respect, she has been already hugged by her grandma, who cried:"my sweety!". The surrounding maids all cried, as well as Dai Yu. The crowds slowy persuade her, and Dai Yu then showed her respect to her grandma.--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 14:01, 19 December 2021 (UTC)

==罗曦 Luó Xī 英语语言文学（英美文学）女 202120081512==

贾母方一一指与黛玉道：“这是你大舅母。这是二舅母。这是你先前珠大哥的媳妇珠大嫂子。”黛玉一一拜见。贾母又说：“请姑娘们。今日远客来了，可以不必上学去。”众人答应了一声，便去了两个。

Baoyu's grandmother than introduce them respectively:"This is your eldest aunt, and this is your second aunt.This is your Zhu brother's wife. Dai Yu greet them one by one.Baoyu's grandmother than said that:"Invite the gilrs. Today here come the dear guest, so they don't need to go to school." Surrounding people said yes, and two of them left.

The Lady Dowager then introduced them respectively to Daiyu: "This is your eldest aunt, and this is your second uncle's wife. This is your deceased elder brother Zhu's wife." Daiyu greeted them one by one. Her grandmother then said: "Tell all the girls to come here. We have visitor who came from afar, so they don't need to go to school." Surrounding people answered yes, and two of them left to call them.--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 07:22, 20 December 2021 (UTC)

==马新 Mǎ Xīn 外国语言学及应用语言学女 202120081513==

不一时，只见三个奶妈并五六个丫鬟，拥着三位姑娘来了：第一个肌肤微丰，身材合中，腮凝新荔，鼻腻鹅脂，温柔沉默，观之可亲；第二个削肩细腰，长挑身材，鸭蛋脸儿，俊眼修眉，顾盼神飞，文彩精华，见之忘俗；

In a little while, three grannies and five or six servant girls turned up, clustering with three ladies. The first was somewhere plump in figure and of average height; her cheek was in beautiful shape, like a fresh lichee; her nose was glossy like the goose grease; she was gentle and quiet in nature, who looks very friendly. The second was thin and tall with an oval face, sparking eyes and long eyebrows; her elegance and quick-witted mind tickle people’s fancy, letting them forget everything vulgar.--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 08:11, 11 December 2021 (UTC)

After a while, the three young ladies showed up, escorted by three wet nurses and five or six maids. The first was slightly plump and of medium height; her cheeks were as smooth and soft as the newly ripened lichees, and her nose was as glossy as goose fat. She was tender and reticent, and looked very affable. The second had drooping shoulders and a slender waist; she was tall and slim, with an oval face, bright and piercing eyes as well as delicate eyebrows. She seemed elegant, quick-witted and in high spirits, with a display of distinctive charm. People who looked at her were to forget everything vulgar and tawdry.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 23:42, 11 December 2021 (UTC)

==毛雅文 Máo Yǎwén 英语语言文学（英美文学）女 202120081514==

第三个身量未足，形容尚小：其钗环裙袄，三人皆是一样的妆束。黛玉忙起身，迎上来见礼，互相厮认，归了坐位。丫鬟送上茶来。不过叙些黛玉之母如何得病，如何请医服药，如何送死发丧。不免贾母又伤感起来，因说：“我这些女孩儿，所疼的独有你母亲。

The third one was not yet fully grown, and she still had the face of a child. All the three young ladies were dressed in similar garments, that is, the tunics and the skirts with the same bracelets and head ornaments. Daiyu hastily rose to greet politely these cousins, and then they introduced to and acquainted with each other, after which they took seats while the maids served the tea. All their talk now was about Daiyu's mother: the culprit for her illness, the medicine that the doctors prescribed for treating her disease, and the conduction of her funeral and mourning ceremonies. Inevitably, the Lady Dowager couldn't help being affected painfully. "Of all my chilren I loved your mother best," she told Daiyu.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 07:49, 11 December 2021 (UTC)

==毛优 Máo Yōu 俄语语言文学女 202120081515==

今一旦先我而亡，不得见面，怎不伤心！”说着，携了黛玉的手，又哭起来。众人都忙相劝慰，方略略止住。众人见黛玉年纪虽小，其举止言谈不俗；身体面貌虽弱不胜衣，却有一段风流态度，便知他有不足之症。

Once she died before me, I could not see her again. She said, taking Mascara Jade Forest's hand, and cried again. Everyone was busy trying to console her, and soon she slightly stopped. They saw that although Mascara Jade Forest was young, her manner and speech were not ordinary; although her health was weak, she had graceful and elegant manner, so they knew that she had a disease of deficiency.--[[User:Mao You|Mao You]] ([[User talk:Mao You|talk]]) 08:43, 11 December 2021 (UTC)

"Once she died before me, it is so sad that I could not see her again." she said, taking Mascara Jade Forest's hand, and cried again. Everyone was trying to console her, and then she slightly stopped. They saw that although Mascara Jade Forest was young, her manner and speech were not ordinary; although she was weak, she had graceful and elegant gestures, so they learned that she had a disease of deficiency.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 06:35, 12 December 2021 (UTC)

==牟一心 Móu Yīxīn 英语语言文学（英美文学）女 202120081516==

因问：“常服何药？为何不治好了？”黛玉道：“我自来如此，从会吃饭时便吃药到如今了，经过多少名医，总未见效。那一年我才三岁，记得来了一个癞头和尚，说要化我去出家，我父母自是不从。

So they asked:" What medicine do you usually take? Why doesn't it work?" Mascara Jade Forest replied:" I am used to getting along with my disease. I have been taking medicine since I could eat. A lot of famous daocters cannot contribute to my illness.When I was three years old, a monk with favus on the head came to persuade me to become a nun,but my parents declined him.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 08:07, 11 December 2021 (UTC)

They then asked, "What medicines do you take regularly? Why can't you cure your illness?" Mascara Jade Forest, "I am used to getting along with my disease. I have been taking medicine since I could eat. A lot of famous docters cannot contribute to my illness. I was only three years old when I remember a mangy monk came and said he wanted to convert me to a monk, but my parents refused.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 06:29, 13 December 2021 (UTC)

==彭瑞雪 Péng Ruìxuě 法语语言文学女 202120081517==

他又说：‘既舍不得他，但只怕他的病，一生也不能好的；若要好时，除非从此以后，总不许见哭声，除父母之外，凡有外亲，一概不见，方可平安了此一生。’这和尚疯疯癫癫，说了这些不经之谈，也没人理他。

The monk said, "if you can't bear to part with her she'll probably nerver get well. The only remedy is to keep her from hearing weeping and from seeing any relatives apart from her father and mother. That's her only hope of having a quiet life." No one paid any attention, of course, to such crazy talk.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 06:24, 13 December 2021 (UTC)

The monk said, "if you can't bear to separate with her, she'll probably nerver get well. The only remedy is to keep her from hearing weeping and from seeing any relatives apart from her father and mother. That's her only hope of having a quiet life." No one paid any attention, of course, to such nonsense talk.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 12:12, 19 December 2021 (UTC)

[[Media:Example.ogg]]==秦建安 Qín Jiànān 外国语言学及应用语言学女 202120081518==

如今还是吃人参养荣丸。”贾母道：“这正好，我这里正配丸药呢，叫他们多配一料就是了。”一语未完，只听后院中有笑语声，说：“我来迟了，没得迎接远客。”黛玉思忖道：“这些人个个皆敛声屏气如此，这来者是谁，这样放诞无礼？”

Now Mascara Jade Forest is still taking ginseng pills.And Grandma Merchant said:" What a coincidence! The pills are making now, I just tell them to add one." The words have not been finished, but there is a laugh in the back yard, which said:" I come late and fail to welcome our distinguished guest." Mascara Jade Forest thought: all people here are holding their breath, who is this person that is so arrogant and rude?--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 08:19, 11 December 2021 (UTC)

Now Lin Daiyu is still taking ginseng pills. And Grandma Merchant said:" It just so happens that I have been asking them to dispense the pills, just asking them to do one more portion." The words are not finished, but there is a laugh in the back yard, which said:" I am late and fail to welcome our distinguished guest." Mascara Jade Forest thought: “all people here are holding their breath, who is this person that is so arrogant and rude?”--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 09:33, 12 December 2021 (UTC)

==邱婷婷 Qiū Tíngtíng 英语语言文学（语言学）女 202120081519==

心下想时，只见一群媳妇、丫鬟拥着一个丽人，从后房进来。这个人打扮与姑娘们不同，彩绣辉煌，恍若神妃仙子：头上戴着金丝八宝攒珠髻，绾着朝阳五凤挂珠钗；项上戴着赤金盘螭缨络圈；身上穿着缕金百蝶穿花大红云缎窄褃袄，外罩五彩刻丝石青银鼠褂；

While Mascara Jade Forest is still thinking about it, a group of daughters-in-law and maids cluster around a beauty coming in from the back room. She dresses up differently from other girls, with colorful embroidery splendor, and looks like a divine concubine or a fairy: wearing a gold silk beads bun decorated with eight treasures and the five phoenix hairpin hanging with beads on the head; a red gold coiled chi dragon tassel ring around the neck; the bright red made of cloud satin material narrow lining cotton jacket with decorations of wisps of gold hundred butterflies and flowers, and the outer coat with decorations of the multicolored engraved silk stone green silver mouse. --[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 09:34, 12 December 2021 (UTC)

Mascara Jade Forest was still thinking about it when she saw a group of daughters-in-law and maids embracing a beautiful woman who came in from the back room. This woman dresses differently from the girls, with colorful embroidery splendor, and looks like a divine concubine fairy: wearing a gold silk eight treasure save beads bun and the sunrise five phoenix hanging beads hairpin on the head; a red gold coiled chi dragon tassel ring around the neck; wearing the bright red made of cloud satin material narrow lining cotton jacket with decorations of wisps of gold hundred butterflies and flowers, and the outer coat with decorations of the multicolored engraved silk stone green silver mouse.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 07:47, 11 December 2021 (UTC)

==饶金盈 Ráo Jīnyíng 英语语言文学（语言学）女 202120081520==

下着翡翠撒花洋绉裙。一双丹凤三角眼，两弯柳叶吊梢眉。身量苗条，体格风骚。粉面含春威不露，丹唇未启笑先闻。黛玉连忙起身接见。贾母笑道：“你不认得他。他是我们这里有名的一个泼辣货，南京所谓‘辣子’，你只叫他‘凤辣子’就是了。”

Splendid Pheonix King wore a jadeite flowered dress underneath, with a pair of phoenix triangle eyes and two curved willow hanging eyebrows. Her figure is slim and her physique is flirtatious. She can be described with “ the face is delicate and beautiful, spirited character of her is not revealed in the appearance, red lips beautiful, not yet open mouth first heard her laugh”. Mascara Jade Forest hastily got up to curtsy to her. Grandma Merchant said with a smile, "You do not recognize her. She is famous for her boldness and vigorousness here, she is truly the 'chilli woman' in Nanjing dialect, you can just call her ' chilli Feng'."--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 07:35, 11 December 2021 (UTC)

Splendid Pheonix King, characterized by a pair of phoenix triangle eyes and two curved willow hanging eyebrows, wore an emerald flowered crepe skirt. She was slender and coquettish, with a delicate face and a smiling lip. Mascara Jade Forest promptly rose quickly to greet her. Grandma Merchant said with a smile: “ you don’t know him. He is famous for her fierceness and toughness, namely the so-called Nanjing chilli. So you can just call him ‘Chilli Pheonix’.”--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 12:48, 11 December 2021 (UTC)

==石丽青 Shí Lìqīng 英语语言文学（英美文学）女 202120081521==

黛玉正不知以何称呼，众姊妹都忙告诉黛玉道：“这是琏二嫂子。”黛玉虽不曾识面，听见他母亲说过：大舅贾赦之子贾琏，娶的就是二舅母王氏的内侄女，自幼假充男儿教养，叫做王熙凤学名。黛玉忙陪笑见礼，以“嫂”呼之。

Mascara Jade Forest was insensible of what to call her. Then her sisters told her promptly: “ this is your sister-in-law Romance Second Merchant.” Although Mascara Jade Forest had never met her, she heard of her from his mother: Romance Merchant, the son of her Uncle Pardon Merchant, had married the niece of Aunt King, named scientifically Splendid Phoenix King, was brought up as a male offspring since childhood. Mascara Jade Forest was engaged in smiling and saluting at her, calling her “sister-in-law”.--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 12:32, 11 December 2021 (UTC)

Daiyu didn't know what to call her. Then her sisters told her promptly: “This is your sister-in-law Lian Er.” Although Daiyu had never met her, she heard of her from his mother: Jia Lian, the son of her Uncle Jia She, had married the niece of Aunt Wang.She was brought up as a male offspring since childhood and her academic name is Wang Xifeng. Daiyu was engaged in smiling and saluting at her, calling her “sister-in-law”.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 01:55, 13 December 2021 (UTC)

==孙雅诗 Sūn Yǎshī 外国语言学及应用语言学女 202120081522==

这熙凤携着黛玉的手，上下细细打量了一回，便仍送至贾母身边坐下，因笑道：“天下真有这样标致人儿！我今日才算看见了。况且这通身的气派，竟不像老祖宗的外孙女儿，竟是嫡亲的孙女儿似的，怨不得老祖宗天天嘴里心里放不下。

Taking Daiyu's hand, Xifeng looked up and down her carefully, then she sent her to Mother Jia's side to sit down.She laughed and said:"There is really such a beautiful person in the world!I didn't see her until today.Moreover,the style of her makes her be more like your son's daughter than your daughter's daughter.It's no wonder that you are concerned about her so much.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 01:49, 13 December 2021 (UTC)

Taking Mascara Jade Forest's hand, Splendid Phoenix King looked her up and down carefully, then sent her to Grandma Merchant's side to sit down. She laughed and said:"There is really such a beautiful person in the world! I haven’t seen her until today. Moreover, her extraordinary temperament makes her be more like your son's daughter rather than your daughter's daughter. It's no wonder that you are concerned about her so much. --[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 06:48, 13 December 2021 (UTC)

==王李菲 Wáng Lǐfēi 英语语言文学（英美文学）女 202120081523==

只可怜我这妹妹这么命苦，怎么姑妈偏就去世了呢？”说着便用帕拭泪。贾母笑道：“我才好了，你又来招我；你妹妹远路才来，身子又弱，也才劝住了：快别再提了。”

I pity my sister for being so miserable, how could my aunt died so early?" She said, wiping her tears with her handkerchief. Grandma Merchant laughed and said, "I've just recovered. You come to provoke me again. Your sister has just arrived from a long journey and is weak, so she has just been persuaded: Don't mention it again."--[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 02:37, 12 December 2021 (UTC)

I pity my sister who is so miserable, how could my aunt have died?" She said, wiping her tears with her handkerchief. Your sister has only just arrived from a long journey and is weak, so she has only just been persuaded to stop talking about it."--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 08:22, 11 December 2021 (UTC)

==王逸凡 Wáng Yìfán 亚非语言文学女 202120081524==

熙凤听了，忙转悲为喜道：“正是呢，我一见了妹妹，一心都在他身上，又是喜欢，又是伤心，竟忘了老祖宗了。该打，该打！”又忙拉着黛玉的手问道：“妹妹几岁了？可也上过学？现吃什么药？在这里别想家。

The first time I saw my sister, I was all over him, and I liked him, and I was sad, and I forgot about my ancestors. You should be beaten, you should be beaten!" He also took Daiyu's hand and asked, "How old is my sister? How old is she? What kind of medicine do you take now? Don't be homesick here.--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 08:21, 11 December 2021 (UTC)

The first time I saw my sister, I was all over him, and I liked him, and I was sad, and I forgot about my ancestors. You should be beaten, you should be beaten!" He also took Daiyu's hand and asked, "How old is my sister? How old is she? What kind of medicine do you take now? Don't be homesick here.--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 11:14, 22 December 2021 (UTC)

==王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525==

要什么吃的，什么玩的，只管告诉我；丫头、老婆们不好，也只管告诉我。”黛玉一一答应。一面熙凤又问人：“林姑娘的东西可搬进来了？带了几个人来？你们赶早打扫两间屋子，叫他们歇歇儿去。”

Just tell me what you want to eat and play; Girls and old servants are not good, just tell me. " Daiyu nodded one by one. On one side, Xifeng asked, "have you moved in Miss Lin's things? How many people have you brought? Clean the two rooms early and tell them to have a rest."--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 06:54, 12 December 2021 (UTC)

Tell me what you want to eat and play; And if the maids or old nurses aren't good to you, just let me know. " Mascara Jade Forest nodded one by one. At the same time, Splendid Phoenix asked, "Have Miss Forest's things been moved in? And how many people does she bring? Clean the two rooms as soon as possible and tell them to have a rest there."--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 08:24, 12 December 2021 (UTC)

==卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526==

说话时已摆了果茶上来，熙凤亲自布让。又见二舅母问他：“月钱放完了没有？”熙凤道：“放完了。刚才带了人到后楼上找缎子，找了半日，也没见昨儿太太说的那个。想必太太记错了。”王夫人道：“有没有，什么要紧！”

Fruits and tea had been prepared when Splendid Phoenix was talking, and she arranged them by herself. Lady King asked her whether the monthly payment has been given out, she answered yes. “I looked for the satin in the back stairs with some people for hours just now, but didn’t find which madam mentioned yesterday. Madam must be wrong.” Splendid Phoenix King said, and Lady King answered, “ It doesn’t matter if there is or not.”--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 07:45, 12 December 2021 (UTC)

Fruits and tea had been prepared when Xifeng was talking, and she arranged them by herself. The second aunt asked her, "Have the monthly payment been given out?" Xifeng answered, "Yes. And I looked for the satin in the back stairs with some people for hours just now, but didn’t find what madam mentioned yesterday. Madam mabey remember something wrong.” Mrs. Wang replied, “ It doesn’t matter if there is or not.”--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 09:03, 12 December 2021 (UTC)

==魏楚璇 Wèi Chǔxuán 英语语言文学（英美文学）女 202120081527==

因又说道：“该随手拿出两个来，给你这妹妹裁衣裳啊。等晚上想着，再叫人去拿罢。”熙凤道：“我倒先料着了，知道妹妹这两日必到，我已经预备下了。等太太回去过了目，好送来。”

Mrs. Wang said, "You should take out a couple of satin pieces to cut your sister's dress. When you think of this matter in the evening, send someone for the satin ." Xifeng said, "I expected it. I knew my sister would arrive in these two days, and I had already made preparations. I will send someone for the satin as soon as you have returned and examined it."--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 08:52, 12 December 2021 (UTC)

Mrs. Wang added, "You should take out a couple of satin pieces to cut your sister's dress. When you think of this in the evening, send someone for the satin ." Xifeng said, "I have expected it. I know my sister will arrive in these two days, and I have already made preparations. I will send someone for the satin as soon as you have examined it."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 13:58, 12 December 2021 (UTC)

==魏兆妍 Wèi Zhàoyán 英语语言文学（英美文学）女 202120081528==

王夫人一笑，点头不语。当下茶果已撤，贾母命两个老嬷嬷带黛玉去见两个舅舅去。维时贾赦之妻邢氏忙起身笑回道：“我带了外甥女儿过去，到底便宜些。”

Her Ladyship smiled, nodded and said nothing. Now the refreshments were cleared away and the Lady Dowager ordered two nurses to take Daiyu to see her two uncles. At this time, Mrs. She also immediately stood up, replied with smile, "it's also very convenient for me to take my niece."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 13:51, 11 December 2021 (UTC)

Her Ladyship smiled, nodded but said nothing. Now the refreshments were cleared away and the Lady Dowager ordered two mothers to take Daiyu to see her two uncles. At this time, Mrs. She immediately stood up, replied with a smile, "it's also very convenient for me to take my niece."--[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 08:37, 12 December 2021 (UTC)

==吴婧悦 Wú Jìngyuè 俄语语言文学女 202120081529==

贾母笑道：“正是呢，你也去罢，不必过来了。”那邢夫人答应了，遂带着黛玉，和王夫人作辞，大家送至穿堂。垂花门前早有众小厮拉过一辆翠幄青油车来，邢夫人携了黛玉坐上，众老婆们放下车帘，方命小厮们抬起。

Jiamu laughed and said: “ Yeah, you can also leave, and don’t have to come here.” Ms. Xing promised, and said goodbye to Ms Wang with Daiyu, all of them went through the hallway. The ingenious green carriage, which drove by a group of manservants stood in front of the floral-pendant gates, Ms. Xing set in the car with Daiyu, several old mothers put down the car shade, instructing boys uplift the carriage. --[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 08:35, 12 December 2021 (UTC)
The mother laughed and said, "Exactly, you also go, no need to come." That Mrs. Xing agreed, so took Daiyu, and Mrs. Wang to say goodbye, we sent to the wear hall. The tent green oil carriage in front of the flower gate, Mrs. Xing took Daiyu to sit on it, the wives put down the curtain, and ordered the boys to lift it.--[[User:Wu Yinghong|Wu Yinghong]] ([[User talk:Wu Yinghong|talk]]) 01:13, 13 December 2021 (UTC)

==吴映红 Wú Yìnghóng 日语语言文学女 202120081530==

拉至宽处，驾上驯骡，出了西角门往东，过荣府正门，入一黑油漆大门内，至仪门前方下了车。邢夫人挽着黛玉的手进入院中。黛玉度其处必是荣府中之花园隔断过来的。
Pulled to a wide place, driving on the tame mule, out of the west corner gate to the east, past the main gate of Rongfu, into a black-painted gate, to the front of the ceremony door down the car. Mrs. Xing took Daiyu's hand and entered the courtyard. The first thing you need to do is to get to the garden.

Then he took the mule，went out the west Corner gate to the east, passed the main gate of Rongfu, entered a black painted gate, and got off in front of Yi gate. Lady Xing took Daiyu's hand and entered the courtyard. Daiyu spent its place must be the garden in the rong mansion partition come over.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 01:38, 15 December 2021 (UTC)

==肖毅瑶 Xiāo Yìyáo 英语语言文学（英美文学）女 202120081531==

进入三层仪门，果见正房、厢房、游廊悉皆小巧别致，不似那边的轩峻壮丽，且院中随处之树木山石皆好。及进入正室，早有许多艳妆丽服之姬妾、丫鬟迎着。邢夫人让黛玉坐了；一面令人到外书房中请贾赦。

When we entered the three-story ceremonial gate, the main room, wing room and verandah were all small and unique, unlike those of the other side. Besides, the trees, mountains and stones in the courtyard were all good. When they entered the main room, there were many concubines and servant girls dressed in colourful makeup and beautiful clothes waiting for them. Madam Xing asked Daiyu to sit down and then let others invite Jia She in the outer study.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 01:02, 15 December 2021 (UTC)

When entering the three- layers ceremonial gate, Daiyu found that the main room, wing room and verandah were all small and unique, unlike those of the other side. Besides, the trees, mountains and stones in the courtyard were all good. When they entered the main room, there were many concubines and servant girls dressed in heavy makeup and beautiful clothes waiting for them. Madam Xing asked Daiyu to sit down and then let others invite Jia She in the outer study.--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 12:10, 19 December 2021 (UTC)

==谢佳芬 Xiè Jiāfēn 英语语言文学（英美文学）女 202120081532==

一时回来说：“老爷说了：‘连日身上不好，见了姑娘，彼此伤心，暂且不忍相见。劝姑娘不必伤怀想家，跟着老太太和舅母，是和家里一样的。姐妹们虽拙，大家一处作伴，也可以解些烦闷。或有委屈之处，只管说，别外道了才是。’”

Mrs.Xing came back and said, "the master said, 'I've been felt not so good for days. I am afraid that I will be emotional if I see you, so I can't bear to see you for the time being. I advise you not to be homesick. It's the same as home to follow the old lady and aunt. Although the sisters are clumsy, you can relieve some boredom if you keep company together. If you have grievances, just tell us and make yourself at home.''--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 12:07, 19 December 2021 (UTC)

Mrs.Xing came back and said, "the master said, 'I've been felt not so good for days. I am afraid that I will be emotional if I see you, so I can't bear to see you for the time being. I advise you not to be homesick. It's the same as home to follow the old lady and aunt. Although the sisters are clumsy, you can relieve some boredom if you keep company together. If you have grievances, just tell us and make yourself at home.''--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:45, 20 December 2021 (UTC)

==谢庆琳 Xiè Qìnglín 俄语语言文学女 202120081533==

黛玉忙站起身来，一一答应了。再坐一刻便告辞，邢夫人苦留吃过饭去。黛玉笑回道：“舅母爱惜赐饭，原不应辞；只是还要过去拜见二舅舅，恐去迟了不恭，异日再领。望舅母容谅。”

Daiyu stood up and agreed one by one. Sitting for a moment and then said goodbye, Mrs. Xing painstakingly stay to eat a meal. Daiyu smile back: "aunt love to give rice, should not resign; just have to go over to see second uncle, afraid to go late disrespectful, another day to receive. I hope aunt forgive me."--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:44, 20 December 2021 (UTC)

==熊敏 Xióng Mǐn 英语语言文学（英美文学）女 202120081534==

邢夫人道：“这也罢了。”遂命两个嬷嬷用方才坐来的车送过去。于是黛玉告辞。邢夫人送至仪门前，又嘱咐了众人几句，眼看着车去了方回来。一时黛玉进入荣府，下了车，只见一条大甬路直接出大门来。

Mrs. Xing said: “That’s fine.” So she ordered two Sisters to send Daiyu back by Carriage used before. So Daiyu farewell others. Mrs. Xing saw her off and said some words to others, seeing the carriage come back and forth. Once Daiyu entered The House of Rong and got off the carriage, she saw a long and wide road.

Mrs. Xing said: “That’s fine.” So she ordered two Sisters to send Daiyu back by Carriage used before. So Daiyu farewell others. Mrs. Xing saw her off to the gate of etiquetteand said some words to others, seeing the carriage come back and forth. Once Daiyu entered The House of Rong and got off the carriage, she saw a long and wide road.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 11:26, 20 December 2021 (UTC)

==徐敏赟 Xú Mǐnyūn 语言智能与跨文化传播研究男 202120081535==

众嬷嬷引着，便往东转弯，走过一座东西穿堂，向南大厅之后，仪门内大院落：上面五间大正房，两边厢房，鹿顶耳房钻山，四通八达，轩昂壮丽，比各处不同。黛玉便知这方是正内室。

Led by the mammy, she turned east, passed through an east-west hall, and came to the south hall, where she found a large courtyard inside the Gate of Yi: five main rooms on the top, flanks on both sides, and deer's roof and ears, extending in all directions, magnificent and different from other places. Daiyu knew this was the inner room.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 09:10, 18 December 2021 (UTC)

Led by the mammies, they turned eastward and passed through an east-west hallway and the southward hall, she found a large courtyard inside the secondary gate: five main rooms on the top, flanks on both sides, and a small flat topped house next to the main house, extending in all directions, magnificent and different from other places. Daiyu knew this was the inner room.--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 10:08, 18 December 2021 (UTC)

==颜静 Yán Jìng 语言智能与跨文化传播研究女 202120081536==

进入堂屋，抬头迎面先见一个赤金九龙青地大匾，匾上写着斗大三个字，是“荣禧堂”；后有一行小字：“某年月日书赐荣国公贾源”，又有“万幾宸翰”之宝。大紫檀雕螭案上，设着三尺多高青绿古铜鼎，悬着待漏随朝墨龙大画，一边是錾金彝，一边是玻璃盆。

Entering the main room, I looked up and saw a great blue board framed in gilded dragons. On the plaque, there were two big words "Rongxi hall"; Then there is a line of small characters: "on a certain date, this was given to Jia Yuan, the Duke of Honor", and there was the treasure of Emperor's handwriting. On the large red sandalwood table that carved with dragon, there was a green bronze tripod more than three feet high, hanging a large ink dragon painting that seemed to attend the imperial court session in the early morning, with gilded wine vessels on one side and a glass basin on the other.--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 08:11, 18 December 2021 (UTC)

there was a green bronze tripod more than three feet high, hanging a large ink dragon painting that seemed to attend the imperial court session in the early morning, with gilded wine vessels on one side and a glass basin on the other.--[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 12:05, 19 December 2021 (UTC)

==颜莉莉 Yán Lìlì 国别女 202120081537==

地下两溜十六张楠木圈椅。又有一副对联，乃是乌木联牌镶着錾金字迹，道是：座上珠玑昭日月，堂前黼黻焕烟霞。下面一行小字是“世教弟勋袭东安郡王穆莳拜手书”。原来王夫人时常居坐宴息也不在这正室中，只在东边的三间耳房内。

On the ground two rows of 16 nanmu armchairs. There is also a pair of couplets, ebony couplet inset with gold handwriting, it said:The pearl and jade in the seat can shine with the sun and the moon; The people in front of the lobby wearing official clothes, its colors like clouds like clouds. The next line is written by Mu Shi, the hereditary king of Dongpyeong County, who is a brother who has been taught by your family for generations.For Lady King often sat and reposed not in this main room, but in the three eastern rooms.--[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 03:36, 12 December 2021 (UTC)

Since Lady King seldom sat in this main hall but used three rooms on the east side for relaxation.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 10:04, 14 December 2021 (UTC)

==颜子涵 Yán Zǐhán 国别女 202120081538==

于是嬷嬷们引黛玉进东房门来。临窗大炕上铺着猩红洋毯，正面设着大红金钱蟒引枕，秋香色金钱蟒大条褥；两边设一对梅花式洋漆小几：左边几上摆着文王鼎，鼎旁匙箸、香盒；右边几上摆着汝窑美人觚，里面插着时鲜花草。

So that the nannies led Mascara Jade Forest through the door of the eastern wing. The large kang by the window was covered with a scarlet foreign rug. In the middle were red back-rests and turquoise bolsters, both with dragon-design medallions, and a long greenish yellow mattress also with dragon medallions. On the two sides， stood one of a pair of small teapoys of foreign lacquer of plum-blossom pattern. On the left-hand table were a tripod, spoons, chopsticks and an incense container; On the right-hand table were a slender-waisted porcelain vase from the Ruzhou Kiln in which were placed seasonable flowers.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 09:48, 14 December 2021 (UTC)

Thereupon,the nurses led Daiyu through the door of the eastern wing. The large kang by the window was covered with a scarlet foreign rug. In the middle were red back-rests and turquoise bolsters, both with dragon-design medallions, and a long greenish yellow mattress also with dragon medallions. On the two sides stood on a pair of small teapoys of foreign lacquer of plum-blossom pattern. On the left-hand table were a tripod, spoons, chopsticks and an incense container; On the right-hand table were a slender-waisted porcelain vase from the Ruzhou Kiln in which were placed seasonable flowers.--[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 13:47, 14 December 2021 (UTC)

==阳佳颖 Yáng Jiāyǐng 国别女 202120081540==

地下面，西一溜四张大椅，都搭着银红撒花椅搭，底下四副脚踏；两边又有一对高几，几上茗碗、瓶花俱备。其馀陈设，不必细说。老嬷嬷让黛玉上炕坐。炕沿上却也有两个锦褥对设。

On the floor on the west side of the room, were four chairs in a row, all of which were covered with antimacassars, embroidered with silverish-red flowers.Beneath them stood four footstools. On either side, was also a pair of high teapoys which were covered with teacups and flower vases.The rest of the room need not be described in detail.
The nannies urged Mascara Jade Forest to sit on the kang, on the edge of which were two brocade cushions. --[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 13:42, 14 December 2021 (UTC)

On the floor facing on the west wall were four chairs in a row, all of which were covered with ornamented cloth embroidered with silverish-red flowers.Beneath them stood four footstools. On either side were a pair of high table with teacups and flower vases.Other decorations in the rest of the room need not be described in detail.The nannies urged Mascara Jade Forest to sit on the kang, on the edge of which were two brocade cushions.--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 09:50, 18 December 2021 (UTC)

==杨爱江 Yáng Àijiāng 英语语言文学（语言学）女 202120081541==

黛玉度其位次，便不上炕，只就东边椅上坐了。本房的丫鬟忙捧上茶来。黛玉一面吃了，打量这些丫鬟们妆饰衣裙，举止行动，果与别家不同。

Considering her status in the family, Daiyu sat on one of the chairs on the east side instead of sitting on the ''kang''. The maids in attendance served tea immediately. When she was sipping the tea, she observed the maids’ make-up,clothes and deportment, which, her thought, were indeed quite different from those in other families.--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 09:38, 18 December 2021 (UTC)

Considering her status in the family, Mascara Jade sat on one of the chairs on the east side instead of sitting on the ''kang''. The maids in attendance served tea immediately.Sipping the tea, she observed the maids’ make-up,clothes and deportment, which, her thought, were indeed quite different from those in other families.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 14:18, 18 December 2021 (UTC)

==杨堃 Yáng Kūn 法语语言文学女 202120081542==

茶未吃了，只见一个穿红绫袄、青绸掐牙背心的一个丫鬟走来笑道：“太太说，请林姑娘到那边坐罢。”老嬷嬷听了，于是又引黛玉出来，到了东廊三间小正房内。

Before the tea was drunk, a servant girl wearing a red silk jacket and a green satin vest came up and smiled, "Mrs. Wang invited Miss Lin to come and sit over there." When the old Mammy heard this, she led Daiyu out again and went to the third small main room on the east porch.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 03:33, 12 December 2021 (UTC)

Before they drank tea over, a servant girl in a red silk jacket and a green satin vest came up and smiled, "Mrs. Wang invited Miss Lin to come and sit over there." When the old Mammy heard this, she led Daiyu out again to the third small main room on the east porch.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 11:10, 12 December 2021 (UTC)

==杨柳青 Yáng Liǔqīng 英语语言文学（英美文学）女 202120081543==

正面炕上横设一张炕桌，上面堆着书籍、茶具；靠东壁面西设着半旧的青缎靠背、引枕。王夫人却坐在西边下首，亦是半旧青缎靠背、坐褥。见黛玉来了，便往东让。

On the kang there was a kang table on which books and tea sets piled up. Half new backrests and pillows made of blue satins were set on the east side of the wall. However, Mrs. Wang set at the foot of the west wall where half new backrests and mattresses made of blue satins were displayed. Mrs. Wang moved to the east side when she saw Lin Daiyu come in.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 11:11, 12 December 2021 (UTC)

On the kang lies a kang table,on which books and tea sets are piled up. Half new backrests and pillows made of blue satins were put on the east side of the wall. However, Mrs. Wang sat at the foot of the west wall where half new backrests and mattresses made of blue satins are displayed. Mrs. Wang moved to the east side when she saw Daiyu coming in.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 12:11, 19 December 2021 (UTC)

==叶维杰 Yè Wéijié 国别男 202120081544==

黛玉心中料定这是贾政之位。因见挨炕一溜三张椅子上也搭着半旧的弹花椅袱，黛玉便向椅上坐了。王夫人再三让他上炕，他方挨王夫人坐下。王夫人因说：“你舅舅今日斋戒去了，再见罢。

Daiyu thought it must be Jia Zhen's seat. Seeing that there were half-old bouncing chair blankets on the three chairs slid by the kang, Daiyu sat on the chair. Mrs. Wang repeatedly asked him to go to the kang, then she sat down next to Mrs. Wang. Mrs. Wang said: "Your uncle has gone fast today, goodbye.

Mascara Jade thought that this was Master Merchant's seat， because she saw that there were three chairs next to the bed with a half-used chair, so Mascara Jade sat down on the chair. She sat down next to Lady King after she had asked her to go to the bed again and again. Lady King said, "Your uncle went to fast today, see you later.”--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 12:29, 19 December 2021 (UTC)Yi Yangfan

==易扬帆 Yì Yángfān 英语语言文学（英美文学）女 202120081545==

只是有句话嘱咐你：你三个姐妹倒都极好，以后一处念书认字，学针线，或偶一玩笑，却都有个尽让的。我就只一件不放心：我有一个孽根祸胎，是家里的混世魔王，今日因往庙里还愿去，尚未回来，晚上你看见就知道了。

I just have one thing to tell you: your three sisters are all very good, and in the future they will study and learn to read and write together, and learn to sew, or occasionally play jokes, but all of them will do their best. There is only one thing I am not sure about: I have a sinful child who is the evil one in my family, and he has not returned yet because he has gone to the temple to pay his respects.--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 02:19, 13 December 2021 (UTC)Yi Yangfan

I just want to remind you: your sisters are very kind , and in the future you will study together, and learn to read and write and learn to sew. Sometimes you will play jokes at each other, but you will be very tolerant to each other. There is only one thing I am worried about: there is a naughty boy in our family, and he has not returned yet because he has gone to the temple to redeem his wishes, you will see him in the evening.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 07:45, 13 December 2021 (UTC)

==殷慧珍 Yīn Huìzhēn 英语语言文学（英美文学）女 202120081546==

你以后总不用理会他，你这些姐姐妹妹都不敢沾惹他的。”黛玉素闻母亲说过：“有个内侄，乃衔玉而生，顽劣异常，不喜读书，最喜在内帏厮混。外祖母又溺爱，无人敢管。”

“You can ignore him later and none of your sisters dare to bother him. ” Daiyu heard from her mother: “I have a nephew, who was born with jade in his mouth. He is very naughty and don’t like to read, but prefer to play with girls. His grandma has always spoiled him so that everyone let him be. ”--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 07:27, 13 December 2021 (UTC)

"You can ignore him in future because none of your sisters dare to mess up with him". Mascara Jade has long heard from her mother about him: "I have a nephew, born with a jade in his mouth, who is very naughty and doesn’t like to read, but prefers to hang around with girls. His grandma has always spoiled him so that everyone let him be". --[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 12:31, 19 December 2021 (UTC)

==殷美达 Yīn Měidá 英语语言文学（语言学）女 202120081547==

今见王夫人所说，便知是这位表兄。一面陪笑道：“舅母所说，可是衔玉而生的？在家时，记得母亲常说：这位哥哥比我大一岁，小名就叫宝玉，性虽憨顽，说待姊妹们却是极好的。

What Lady King described today is the cousin for sure. Mascara Jade said while smiling:" Is the person you just mentioned my cousin born with a jade? I remember when I was at home my mother often said that the cousin nicknamed Precious Jade is one year older than me. Although he is a little mischievous, he is very friendly with his sisters".--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:27, 12 December 2021 (UTC)

Who Lady King described today is the cousin for sure. Mascara Jade said while smiling:" Is this my cousin you just mentioned born with a jade? I remember when I was at home my mother often said that the cousin nicknamed Precious Jade is one year older than me. Although he is a little mischievous, he is very friendly with his sisters".--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 12:06, 19 December 2021 (UTC)

==尹媛 Yǐn Yuán 英语语言文学（英美文学）女 202120081548==

况我来了，自然和姊妹们一处，弟兄们是另院别房，岂有沾惹之理？”王夫人笑道：“你不知道原故。他和别人不同，自幼因老太太疼爱，原系和姐妹们一处娇养惯了的。

Now I come here,undoubtfully I live with my sisters. The brothers are in some different houses. Is there any reason to mess with them?" Lady King smiled and said, "You don't know. Unlike the others, he had been coddled by his sisters since he was young for the love of Grandma Merchant.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 15:30, 13 December 2021 (UTC)

Now I come here,undoubtfully I live with my sisters. The brothers are in some different houses. Is there any reason to mess with them?" Lady King smiled and said, "You don't know the reason. Unlike others, he had been coddled by his sisters since he was young for the love of Grandma Merchant.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 03:20, 15 December 2021 (UTC)

==詹若萱 Zhān Ruòxuān 英语语言文学（英美文学）女 202120081549==

若姐妹们不理他，他倒还安静些；若一日姐妹们和他多说了一句话，他心上一喜，便生出许多事来：所以嘱咐你别理会他。他嘴里一时甜言蜜语，一时有天没日，疯疯傻傻，只休信他。”黛玉一一的都答应着。

“If the sisters ignore him, he is a bit quieter: if one day the sisters talk to him more, he is so happy that he will stir up many troubles: so I tell you to ignore him. He may talk sweetly for a while, and he may be crazy and silly for a while, just don't believe him.” Daiyu replied one by one.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 08:45, 13 December 2021 (UTC)
If the sisters ignore him, he will be quiet; if one day they talk to him more, he will be happy, and many things will happen: so I tell you to ignore him. His mouth a sweet talk, a moment there is no day, crazy and silly, just do not believe him. Daiyu agreed one by one.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 12:06, 19 December 2021 (UTC)

==张秋怡 Zhāng Qiūyí 亚非语言文学女 202120081550==

忽见一个丫鬟来说：“老太太那里传晚饭了。”王夫人忙携了黛玉，出后房门，由后廊往西，出了角门，是一条南北甬路，南边是倒座三间小小抱厦厅，北边立着一个粉油大影壁，后有一个半大门，小小一所房屋。
Suddenly see a servant girl to say: "old lady there spread supper." Lady King and Mascara Jade Forest went out of the back door, leading from the back corridor to the west and out of the corner gate. There was a north-south corridor, with three small rooms in the south, a big screen wall of powder and oil in the north, and a small house with a half gate behind.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 13:53, 12 December 2021 (UTC)

Suddenly a servant girl said, "the old lady has passed on dinner." Lady King hurriedly took Mascara Jade Pearl out of the back door, from the back porch to the west, out of the corner door. It is a North-South corridor. In the south is the inverted three small balcony halls. In the north is a oil-powdered large shadow wall, followed by a half gate and a small house.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 12:28, 13 December 2021 (UTC)

==张扬 Zhāng Yáng 国别男 202120081551==

王夫人笑指向黛玉道：“这是你凤姐姐的屋子。回来你好往这里找他去，少什么东西，只管和他说就是了。”这院门上也有几个才总角的小厮，都垂手侍立。王夫人遂携黛玉穿过一个东西穿堂，便是贾母的后院了。

Lady King smiled at Mascara Jade Pearl and said: "This is your sister Phoenix's house. If you come back, you can find her here. And if there's anything missing, just tell her." On the gate of the courtyard, there were also several young boys who were only in their childhood, all standing with their hands down. Lady King then took Mascara Jade Pearl through an east-west hall, which was Grandma Merchant's backyard.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 07:30, 11 December 2021 (UTC)

Lady King smiled at Mascara Jade Pearl and said: "This is your sister Phoenix's house. If you come back, you can find her here. And if there's anything missing, just tell her." On the gate of the courtyard,there were also a few young boys on the door of this courtyard, all standing with their hands down.. Lady King then took Mascara Jade Pearl through an east-west hall, which was Grandma Merchant's backyard.

==张怡然 Zhāng Yírán 俄语语言文学女 202120081552==

于是进入后房门，已有许多人在此伺候，见王夫人来，方安设桌椅；贾珠之妻李氏捧杯，熙凤安箸，王夫人进羹。贾母正面榻上独坐，两旁四张空椅。熙凤忙拉黛玉在左边第一张椅子上坐下，黛玉十分推让。

So they entered the back room, where many people were already waiting, and when they saw Lady King coming, they placed the table and chairs; Li, wife of Treasure Merchant, held the cup, Lady King placed the chopsticks, and Splendid Phoenix King drank the soup. Grandma Merchant was sitting alone on a couch, flanked by four empty chairs. Splendid Phoenix King was busy pulling Mascara Jade Forest to sit in the first chair on the left, but Mascara Jade Forest was too embarrassed to sit.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 00:57, 13 December 2021 (UTC)

So they entered the back room, where many people were already waiting, and when they saw Lady King coming, they placed the table and chairs; Li, wife of Treasure Merchant, held the cup, Lady King placed the chopsticks, and Splendid Phoenix King drank the soup. Grandma Merchant was sitting alone on a couch, flanked by four empty chairs. Splendid Phoenix King was busy pulling Mascara Jade Forest to sit in the first chair on the left, but Mascara Jade Forest was too embarrassed to sit.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 03:42, 13 December 2021 (UTC)

==钟义菲 Zhōng Yìfēi 英语语言文学（英美文学）女 202120081553==

贾母笑道：“你舅母和嫂子们是不在这里吃饭的。你是客，原该这么坐。”黛玉方告了坐，就坐了。贾母命王夫人也坐了。迎春姊妹三个告了坐，方上来：迎春坐右手第一，探春左第二，惜春右第二。

Grandama Merchant said with a smile, "your aunt and sister-in-law don't eat here. You are a guest. You should have sat here." Mascara Jade Forest then sat down. Grandama Merchant ordered Lady King to sit down. The three sisters of Spring Pleasure Merchant sat down：Spring Pleasure Merchant sat first on the right hand, Seeking-Spring Merchant second on the left, and Cherishing Spring Merchant second on the right.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 10:36, 11 December 2021 (UTC)

Grandama Merchant said with a smile, "your aunts and sisters-in-law don't eat here. You are a guest. You should have sat here." Mascara Jade Forest then sat down. Grandama Merchant ordered Lady King to sit down. The three sisters of Spring Pleasure Merchant were asked to sit down: Spring Pleasure Merchant sat first on the right hand, Seeking-Spring Merchant second on the left, and Cherishing Spring Merchant second on the right.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 02:02, 12 December 2021 (UTC)

==钟雨露 Zhōng Yǔlù 英语语言文学（英美文学）女 202120081554==

旁边丫鬟执着拂尘、漱盂、巾帕，李纨、凤姐立于案边布让；外间伺候的媳妇、丫鬟虽多，却连一声咳嗽不闻。饭毕，各各有丫鬟用小茶盘捧上茶来。当日林家教女以惜福养身，每饭后必过片时方吃茶，不伤脾胃；

Standing at the table, the servant girls held the horsetail whisks, vessels for mouthwash and handkerchiefs. Silk Plum and Splendid Phoenix King sent dishes, refreshments to guests and invited them to eat. Though there were many servant girls in the outer room, they could not be heard to utter a sound. When the meal was over, each servant girl brought tea with a small tray. Mascara Jade Forest took tea after each meal to keep health and not hurt her spleen and stomach.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 01:55, 12 December 2021 (UTC)

The servant girls are standing at the table with the horsetail whisks, vessels for mouthwash and handkerchiefs. Silk Plum and Splendid Phoenix King sent dishes, refreshments to guests and invited them to eat. Though there were many servant girls in the outer room, they could not be heard to utter a sound. When the meal was over, each servant girl brought tea with a small tray. Mascara Jade Forest took tea after each meal to keep health and not hurt her spleen and stomach.--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 09:23, 13 December 2021 (UTC)

[[Media:Example.ogg]]==周玖 Zhōu Jiǔ 英语语言文学（英美文学）女 202120081555==

今黛玉见了这里许多规矩不似家中，也只得随和些。接了茶，又有人捧过漱盂来，黛玉也漱了口，又盥手毕。然后又捧上茶来，这方是吃的茶。贾母便说：“你们去罢，让我们自在说说话儿。”
Mascara Jade Forest saw many rules here are not like her home. She was also easy-going. After receiving the tea, someone else took a gargle bowl for her. Mascara Jade Forest also rinsed her mouth and finished washing her hands again. Then tea which was for drinking was brought in. Then Grandma Merchant said to servants , "You all go and let's have a talk in our own comfort."

Now Mascara Jade saw many rules here are not like the rules of her home. She can only be easygoing. She caught the teacup. Some domestics came over with a mouthwash basin. Mascara Jade gargled and washed her hands. Then the servant brought back tea, and this was tea for drinking.Then Dowager Lady Jia said to servant, "You all go and let's have a talk in our own comfort."--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 10:47, 13 December 2021 (UTC)

==周俊辉 Zhōu Jùnhuī 法语语言文学女 202120081556==

王夫人遂起身，又说了两句闲话儿，方引李、凤二人去了。贾母因问黛玉念何书，黛玉道：“刚念了《四书》。”黛玉又问姊妹读何书，贾母道：“读什么书，不过认几个字罢了。”

Lady King stood up and said something idle, then led Lady Plum and Splendid Phoenix King to leave. When Dowager Lady Jia asked Mascara Jade what books she had read, Mascara Jade replied, "I just have read the ''Four Books''." When Mascara Jade asked her sisters what books they read, Dowager Lady Jia said, "They don't read anything. They only know a few words."--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 09:25, 13 December 2021 (UTC)

Lady King rose as soon as she heard these words, and having made a few irrelevant remarks, she led the way and left the room along with the two ladies, Mrs. Li and Splendid Phoenix king.Grandma Merchant, having inquired of Mascara Jade what books she was reading, "I have just begun reading the Four Books," Mascara Jade replied. "What books are my cousins reading?" Mascara Jade went on to ask. "Books, you say!" exclaimed Grandma Merchant; "why all they know are a few characters, that's all."--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:15, 15 December 2021 (UTC)

==周巧 Zhōu Qiǎo 英语语言文学（语言学）女 202120081557==

一语未了，只听外面一阵脚步响，丫鬟进来报道：“宝玉来了。”黛玉心想：“这个宝玉，不知是怎样个惫懒人呢。”及至进来一看，却是位青年公子：头上戴着束发嵌宝紫金冠，齐眉勒着二龙戏珠金抹额；

The sentence was barely out of her lips, when a continuous sounding of footsteps
was heard outside, and a waiting maid entered and announced that Precious Jade was
coming. Mascara Jade was speculating in her mind how it was that this Precious Jade had
turned out such a good-for-nothing fellow, when he happened to walk in.
He was, in fact, a young man of tender years, wearing on his head, to hold his
hair together, a cap of gold of purplish tinge, inlaid with precious gems.
Parallel with his eyebrows was attached a circlet, embroidered with gold, and
representing two dragons snatching a pearl.
--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 08:36, 13 December 2021 (UTC)

After a word, only a sound of footsteps outside, the maid came in and reported: "Baoyu is here." Daiyu thought to herself: "This Baoyu, I don't know what a tired lazy person." When she came in, she was a young man. He wears a purple and gold crown with hair inlaid on his head, and his forehead are tied with gold frontlet（The shape is two dragons playing with pearled）.--[[User:Zhou Qing|Zhou Qing]] ([[User talk:Zhou Qing|talk]]) 15:21, 11 December 2021 (UTC)

==周清 Zhōu Qīng 法语语言文学女 202120081558==

一件二色金百蝶穿花大红箭袖，束着五彩丝攒花结长穗宫绦，外罩石青起花八团倭缎排穗褂；登着青缎粉底小朝靴。面若中秋之月，色如春晓之花；鬓若刀裁，眉如墨画，鼻如悬胆，睛若秋波。

A big red arrow sleeve decorated with two-color golden butterfly flowers, is tied with multicolored silk and knotted with long spikes, and is covered with azurite and satin rowed gowns; it wears small green satin and powder-soled boots. The face is as round and beautiful as the moon of Mid-Autumn Festival, the complexion is like a flower of spring dawn; the temples are like a knife cut, the eyebrows are like ink painting, the nose is like a hanging gall, and the eyes are like autumn waves.

A big red arrow sleeve decorated with two-color golden butterfly flowers, is tied with multicolored silk and knotted with long spikes, and is covered with azurite and satin rowed gowns; he wore small green satin and powder-soled boots. The face is as round and beautiful as the moon at mid-autumn, the complexion is like a flower of in spring; the temples as if chiselled with a knife, the eyebrows are like ink painting, the nose is like a a well-cut and shapely nose, and the eyes are like vernal waves.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 06:19, 13 December 2021 (UTC)

==周小雪 Zhōu Xiǎoxuě 日语语言文学女 202120081559==

虽怒时而似笑，即嗔视而有情。项上金螭缨络，又有一根五色丝绦，系着一块美玉。黛玉一见，便吃一大惊，心中想道：“好生奇怪：倒像在那里见过的，何等眼熟！”只见这宝玉向贾母请了安，贾母便命：“去见你娘来。”

His angry look even resembled a smile; his glance was full of sentiment.Round his neck he had a gold dragon necklet with a fringe; also a cord of variegated silk, to which was attached a piece of beautiful jade. When Mascara Jade Forest saw this, she was shocked."How very strange." she was reflecting in her mind; "it would seem as if I had seen him somewhere or other, for his face appears extremely familiar to my eyes;" Precious Jade Merchant greeted Grandma Merchant "Go and see your mother and then come back," remarked her venerable ladyship.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 06:08, 13 December 2021 (UTC)

His angry look somentimes even resembled a smile; his glance was full of sentiment.Round his neck he had a gold dragon necklet with a fringe; also a cord of silk of five colours, to which was attached a piece of beautiful jade. When Mascara Jade Forest saw this, she was shocked and thought to herself: "How strange it is." she was reflecting in her mind; "as if I had seen him somewhere or other, for his face appears extremely familiar to my eyes;" Precious Jade Merchant greeted Lady Dowager "Go and see your mother and then come back."--[[User:Zhu Suzhen|Zhu Suzhen]] ([[User talk:Zhu Suzhen|talk]]) 11:46, 16 December 2021 (UTC)

==朱素珍 Zhū Sùzhēn 英语语言文学（语言学）女 202120081561==

即转身去了。一会再来时已换了冠带：头上周围一转的短发都结成小辫，红丝结束，共攒至顶中胎发，总编一根大辫，黑亮如漆，从顶至梢，一串四颗大珠，用金八宝坠脚；身上穿着银红撒花半旧大袄；仍旧带着项圈、宝玉、寄名锁、护身符等物；

Then turned around and went. He has changed the crown band when coming back for a while: the short hair around the head is braided, the red silk ends, and the hair is gathered up to the top of the fetus. The chief editor is a big braid, black and shiny, from top to tip , A string of four large beads, with gold eight treasures falling to the feet; wearing a silver-red half-old coat with flowers; still wearing collars, gems, locks, amulets, etc.;

He turned away. When he came back later, he had changed his crown belt: the short hair around his head was braided, and the red silk ended. He saved up to the top and middle fetal hair. The chief editor had a big braid, black and bright as paint, a string of four big beads from the top to the tip, and dropped his feet with gold eight treasures; He was wearing a silver red flower sprinkled semi-old coat; Still wearing collars, precious jade, name sending locks, amulets, etc--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 12:56, 16 December 2021 (UTC)

==邹岳丽 Zōu Yuèlí 日语语言文学女 202120081562==

下面半露松绿撒花绫裤，锦边弹墨袜，厚底大红鞋。越显得面如傅粉，唇若施脂；转盼多情，语言若笑。天然一段风韵，全在眉梢；平生万种情思，悉堆眼角。看其外貌，最是极好，却难知其底细。
His lower body showed loose green flower pants, cotton socks and a pair of thick soled red shoes. This makes him look more beautiful. The lips seem to have been powdered with rouge; When he speaks, he often has a smile on his face, and his eyebrows can convey affection. A person's style and temperament, including what he thinks, can be conveyed through his eyes. His appearance is very good-looking, but I don't know whether he has real connotation.

==Nadia 202011080004==

后人有《西江月》二词批的极确，词曰：

==Mahzad Heydarian 玛莎 202021080004==

无故寻愁觅恨，有时似傻如狂。
Seeking sorrow and hate for no reason, sometimes seems stupid and crazy.

==Mariam toure 2020GBJ002301==

纵然生得好皮囊，腹内原来草莽。

==Rouabah Soumaya 202121080001==

潦倒不通庶务，愚顽怕读文章。

I'm not able to get through general affairs, and I'm afraid of reading articles.

==Muhammad Numan 202121080002==

行为偏僻性乖张，那管世人诽谤。
He who behaves in a perverse way has no control over the slander of course.--[[User:Atta Ur Rahman|Atta Ur Rahman]] ([[User talk:Atta Ur Rahman|talk]]) 03:29, 14 December 2021 (UTC)

==Atta Ur Rahman 202121080003==

又曰：富贵不知乐业，贫穷难耐凄凉。
It is also known that wealth does not know pleasure and happiness, and poverty cannot endure loneliness.

==Muhammad Saqib Mehran 202121080004==

可怜辜负好时光，于国于家无望。
Translation: The poor lived up to the good times, and the country was hopeless at home.

==Zohaib Chand 202121080005==

天下无能第一，古今不肖无双。

==Jawad Ahmad 202121080006==

寄言纨袴与膏粱，莫效此儿形状。

English; the author is to give some suggestion to playboys of high official that they do not follow the example of Jia Baoyu.

==Nizam Uddin 202121080007==

却说贾母见他进来，笑道：“外客没见就脱了衣裳了，还不去见你妹妹呢。”

But she said that Mother Jia saw him come in and smiled: "The foreigner took off her clothes without seeing him, so she won't go to see your sister."

==Öncü 202121080008==

宝玉早已看见了一个袅袅婷婷的女儿，便料定是林姑妈之女，忙来见礼。

Precious Jade had already seen a daughter with a gentle posture, thought might be the daughter of Aunt Lin, then hurried to meet her.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 04:17, 13 December 2021 (UTC)

==Akira Jantarat 202121080009==

归了坐细看时，真是与众各别。

When I look at you carefully, I think you are different.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 09:59, 13 December 2021 (UTC)

When I returned to take a closer look, it was really different. --[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 07:41, 12 December 2021 (UTC)

==Benjamin Wellsand 202111080118==

只见：两弯似蹙非蹙笼烟眉，一双似喜非喜含情目。

I saw two bends like the frowning of smoked eyebrows, at first they seemed happy but not really happy, yet affectionate eyebrows. --[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 07:41, 12 December 2021 (UTC)

I saw: two curved eyebrows that looked like a frown, a pair of eyebrows that seemed to be happy or not. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 23:18, 12 December 2021 (UTC)

==Asep Budiman 202111080020==

态生两靥之愁，娇袭一身之病。

The sorrow of the two distresses, the disease of the whole body. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 23:17, 12 December 2021 (UTC)

The sorrow of two distresses, spoiled - the disease of the whole body.------Ei Mon Kyaw [[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:15, 15 December 2021 (UTC)--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:15, 15 December 2021 (UTC)Ei Mon Kyaw

==Ei Mon Kyaw 202111080021==

泪光点点，娇喘微微。

Tears shone a little, and she breathed slightly.--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:47, 15 December 2021 (UTC)Ei Mon Kyaw -----Ei Mon Kyaw[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:47, 15 December 2021 (UTC)
The tears droped, and she breathed slowly. --[[User:Mahzad Heydarian|Mahzad Heydarian]] ([[User talk:Mahzad Heydarian|talk]]) 11:58, 15 December 2021 (UTC)

The eyes twinkled with tears and she breathed slightly.--[[User:Chen Jing|Chen Jing]] ([[User talk:Chen Jing|talk]]) 12:18, 19 December 2021 (UTC)

20211215 homework

2021-12-29T08:57:40Z

Wei Yiwen: /* 王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525 */

Quicklinks: [[Introduction_to_Translation_Studies_2021|Back to course homepage]] [https://bou.de/u/wiki/uvu:Community_Portal#Frequently_asked_questions_FAQ FAQ] [https://bou.de/u/wiki/uvu:Community_Portal Manual] [[20210926_homework|Back to all homework webpages overview]] [[20220112_final_exam|final exam page]]

==陈静 Chén Jìng 国别女 202020080595==

鼎：古代食器。胡羼(chàn忏) ──胡闹。羼：本义为群羊杂居。引申为杂乱不纯，乱七八糟。

Tripod (Ding in Chinese): ancient food utensil. Hu Chan in Chinese means nonsense. Chan in Chinese originally means that the sheep live together, whose extensive meaning is mess.
----

Tripod: ancient food utensil. Hi Chan - nonsense. The original meaning is that sheep live together. It is extended meaning to be messy, impure and messy.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 01:25, 12 December 2021 (UTC)

==蔡珠凤 Cài Zhūfèng 法语语言文学女 202120081477==

抓──即“抓周”，亦称“试儿”、“试周”。旧俗于婴儿满周岁时，父母摆列各种小件器物，任其抓取，以测试其秉性、智愚、志趣。此俗始于江南，后亦传到北方。

Grasping -- namely "grasping the week", also known as "trying the child" and "trying the week". The old custom is that when a baby reaches the age of one year, his parents arrange all kinds of small objects and let him grab them to test his temperament, intelligence and interest. This custom began in the south of the Yangtze River and later spread to the north.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 01:23, 12 December 2021 (UTC)

Catch ─ ─ means "catch the week", also known as "test" and "test week". The old custom is when the baby reaches one year old, the parents arrange all kinds of small utensils and let them grab them to test their disposition, wisdom and ambition. This custom began in the south of the Yangtze River and then spread to the north.--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 07:41, 11 December 2021 (UTC)

==曾俊霖 Zēng Jùnlín 国别男 202120081478==

事见北朝周·颜之推《颜氏家训·风操》：“江南风俗，儿生一期(年)，为制新衣，盥浴装饰，男则用弓矢纸笔，女则刀尺针缕(线)，并加饮食之物及珍宝服玩，置之儿前，观其发意所取，以验贪亷智愚，名之为试儿。”

It is said in Yan's family instructions and customs by Yan Zhitui of the Northern Dynasty that "the custom in the south of the Yangtze River was born in the first year. It was to make new clothes and decorate bathrooms. Men used bows and arrows, paper and pens, women used knives, rulers, needles and threads (lines), and played with food and precious clothes. They were placed in front of their children and looked at what they wanted to take to test their greed, wisdom and stupidity. They were called test children."--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 07:37, 11 December 2021 (UTC)

It is said in Yan's family instructions and customs by Yan Zhitui of ''the Northern Dynasty'' that the custom in the south of the Yangtze River was born in the first year. It was to make new clothes and decorate bathrooms. Men used bows and arrows, paper and pens, women used knives, rulers, needles and threads (lines), and played with food and precious clothes. They were placed in front of their children and looked at what they wanted to take to test their greed, wisdom and stupidity. They were called test children."--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 12:20, 20 December 2021 (UTC)Chen Huini

==陈惠妮 Chén Huìnī 英语语言文学（英美文学）女 202120081479==

(宋·赵彦卫《云麓漫钞》卷二也有相同记载)又宋·叶真《爱日斋丛钞》卷一：“《玉壶野史》记曹武惠王(曹彬)始生周晬日，父母以百玩之具罗于席，观其所取。

(Song · Zhao Yanwei's ''Yunlu Manchao'', Volume 2 has the same record) and Song · Ye Zhen, Volume 1, ''Ai Ri Zhai Cong Chao'': "''In the History of Jade Pot'', when King Cao Wu hui (Cao Bin) was on the year ahead in the first week of his birth, his parents viewed the year he took with a hundred toys on the table.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 12:24, 20 December 2021 (UTC)Chen Huini

（also recorded in Volume 2 of ''Yunlu Essay'' by Zhao Yanwei，Song Dynasty） Volume 1 of ''Ai Rizhai Essay'' by Ye Zhen，Song Dynasty：“ ''History of Jade Pot'' records that King Wuhui（Cao Bin）'s parents put many toys on the table and observed his choice when he was 100 days years old.”--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:53, 22 December 2021 (UTC)

== Headline text ==
==陈湘琼 Chén Xiāngqióng 外国语言学及应用语言学女 202120081480==

武惠王左手提干戈，右手提俎豆，斯须取一印，馀无所视。曹，真定人。江南遗俗乃在此(指真定)，今俗谓试周是也。”

Lord Wuhui holds weapons with his left hand and dinnerware in his right hand.Then he looks at a seal and graps it without seeing anything else.Lord Wuhui, whose first name is Cao, comes from Zhen Ding county. The place is called Shi Zhou now, on whiche Jiang Nan's old cities lay.--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:23, 14 December 2021 (UTC)

Lord Wuhui holds weapons with his left hand and dinnerware in his right hand.Then he looks at a seal and graps it without seeing anything else.Lord Wuhui, whose first name is Cao, comes from Zhen Ding county. The place is so-called Shizhou now, on which ancient Jiangnan lay.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:07, 14 December 2021 (UTC)

==陈心怡 Chén Xīnyí 翻译学女 202120081481==

致知格物──语出《礼记·大学》：“致知在格物，格物而后知至。”意谓要想获得知识，必须探究事物的道理。致：获得，取得。

Zhi Zhi Ge Wu- ''From The Book of Rites·Daxue'': "Zhizhi lies in Gewu, and after Gewu, knowledge arrives." It means that in order to gain knowledge, one must inquire into the truth of things. Zhi: To acquire, to obtain.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:18, 12 December 2021 (UTC)

Zhi Zhi Ge Wu - originated from ''The Book of Rites·Daxue'': "The intention of Zhizhi refers to Gewu, and after the process of Gewu, knowledge will be obtained." It means that in order to gain knowledge, one must inquire into the truth of things. Zhi: to acquire, and to obtain.--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 14:45, 20 December 2021 (UTC)

==程杨 Chéng Yáng 英语语言文学（英美文学）女 202120081482==

格：推究，探究，探讨。尧……张──尧、舜、禹、汤、文、武，即唐尧、虞舜、夏禹、成汤、周文王、周武王，是从上古至西周的明君；
Ge: means deduction, exploration and discussion. Yao...Zhang──Yao, Shun, Yu, Tang, Wen, Wu, namely Tang Yao, Yu Shun, Xia Yu, Cheng Tang, Emperor Wen of Zhou Dynasty, Emperor Wu of Zhou Dynasty, they are all wise emperors from ancient times to the Zhou Dynasty;--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 13:11, 11 December 2021 (UTC)

Ge: means deduction, exploration and discussion. Yao...Zhang──Yao, Shun, Yu, Tang, Wen, Wu, namely Tang Yao, Yu Shun, Xia Yu, Cheng Tang, Emperor Wen of Zhou Dynasty, Emperor Wu of Zhou Dynasty, they are all wise emperors from ancient times to Zhou Dynasty;--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 12:13, 19 December 2021 (UTC)

==丁旋 Dīng Xuán 英语语言文学（英美文学）女 202120081483==

周、召，即周公旦、召公奭，都是西周的贤相；孔、孟，即孔丘(通称孔子)、孟轲(通称孟子)，都是儒学的创始人；董、韩、周、程、朱、张，即汉代董仲舒、唐代韩愈、北宋周敦颐、北宋程颢和程颐兄弟、南宋朱熹、北宋张载，都是儒学理论家。

Zhou, called the Duke of Zhou, and Zhao, called Duke of Shi, are both talented prime ministers (in feudal China); Kong (generally called Confucius) and Meng (generally called Mencius) are both founders of Confucianism; Dong (Dong Zhongshu in Han Dynasty), Han (Han Yu in Tang Dynasty), Zhou (Zhou Dunyi in the Northern Song Dynasty), Cheng (Cheng Jing and Cheng Yi brothers in the Northern Song Dynasty), Zhu (Zhu Xi in the Southern Song Dynasty), Zhang (Zhang Zai in the Northern Song Dynasty) are all Confucian theorists. --[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 07:19, 12 December 2021 (UTC)

Zhou and Zhao are respectively the Duke of Zhou and the Duke of Shi and both are talented prime ministers of the Western Zhou Dynasty; both Kong (generally called Confucius) and Meng (generally called Mencius) are founders of Confucianism; Dong (Dong Zhongshu in Han Dynasty), Han (Han Yu in Tang Dynasty), Zhou (Zhou Dunyi in the Northern Song Dynasty), Cheng (Cheng Jing and Cheng Yi brothers in the Northern Song Dynasty), Zhu (Zhu Xi in the Southern Song Dynasty), Zhang (Zhang Zai in the Northern Song Dynasty) are all Confucian theorists. --[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 08:09, 12 December 2021 (UTC)

==杜莉娜 Dù Lìnuó 英语语言文学（语言学）女 202120081484==

这些人皆是儒家竭力推崇的人物。蚩尤……秦桧──蚩尤、共工，都是传说中上古最凶恶的部族首领；桀、纣、始皇，即夏桀、商纣王、秦始皇，都是登峰造极的暴君；

All these people are strong recommended by confucianists such as Chi You(a mythological warrior engaged in fighting with the Yellow Emperor), Qin Hui (a traitor in the Song dynasty in Chinese history)and so on. Among them both Chi You and Gong Gong (the water god in ancient Chinses history and the devil of floods) are the most ferocious tribal chief in the Chinese legend;and all Xia Jie, Shang Zhou and Qin Shi Huang, being respectively the emperor Jie of Xia Dynasty，the emperor Zhou of Shang Dynasty and the first emperor of Qin Dynasty, are extremely tyrannical.

All these people are strongly recommended by Confucianists such as Chi You(a mythological warrior engaged in fighting with the Yellow Emperor), Qin Hui (a traitor in the Song dynasty in Chinese history)and so on. Among them both Chi You and Gong Gong (the water god in ancient Chinses history and the devil of floods) are the most ferocious tribal chief in the Chinese legend;and all Xia Jie, Shang Zhou and Qin Shi Huang, being respectively the emperor Jie of Xia Dynasty，the emperor Zhou of Shang Dynasty and the first emperor of Qin Dynasty, are extremely tyrannical.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 14:13, 19 December 2021 (UTC)

==付红岩 Fù Hóngyán 英语语言文学（英美文学）女 202120081485==

王莽、曹操、桓温、安禄山、秦桧，他们分别是汉代、三国、东晋、唐代、南宋人，都是大奸臣乃至叛逆之贼。许由……朝云──许由，传说他是上古时为了逃避帝位而终生隐居的贤人；陶潜(即陶渊明)、阮籍、嵇康、刘伶，都是魏晋时期著名文学家及不与流俗同低昂的独行之士；

Wang Mang, Cao Cao, Huan Wen, An Lushan and Qin Kuei, who were in the Han Dynasty, the Three Kingdoms, the Eastern Jin Dynasty, the Tang Dynasty and the Southern Song Dynasty respectively, were all great treacherous court officials and even traitors. It were Xu You... Zhao Yun -- Xu You who were said a sage who lived in seclusion all his life in order to escape the throne in ancient times. Tao Qian (Tao Yuanming), Ruan Ji, Ji Kang and Liu Ling were all prestigious persons in the Wei and Jin dynasties and mavericks who did not flow along with the turbid currents of the mainstream thought.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 14:10, 19 December 2021 (UTC)

Wang Mang, Cao Cao, Huan Wen, An Lushan and Qin Kuei, who were in the Han Dynasty, the Three Kingdoms, the Eastern Jin Dynasty, the Tang Dynasty and the Southern Song Dynasty respectively, were all great treacherous court officials and even traitors. Xu You... Zhao Yun -- Xu You. It is said that he was a sage who lived in seclusion all his life in order to escape the throne in ancient times. Tao Qian (Tao Yuanming), Ruan Ji, Ji Kang and Liu Ling were all famous writers in the Wei and Jin dynasties and mavericks who did not flow along with the turbid currents of the world.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 11:57, 19 December 2021 (UTC)

==付诗雨 Fù Shīyǔ 日语语言文学女 202120081486==

王谢二族，指东晋王导和谢安，都是显贵；顾虎头，即顾恺之，字虎头，是东晋名画家；陈后主、唐明皇、宋徽宗，都是有才气的风流皇帝；

The Two families of Wang and Xie, namely Wang Dao and Xie An, were both nobility in the Eastern Jin Dynasty. Gu Hutou, also known as Gu Kaizhi, was a famous painter in the Eastern Jin Dynasty. Emperor Chen Shubao of Chen, Emperor Ming of Tang and Emperor Huizong of Song were all talented and romantic emperors.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 10:07, 12 December 2021 (UTC)

The Two families of Wang and Xie, namely Wang Dao and Xie An, were both of the nobility in the Eastern Jin Dynasty. Gu Hutou, also known as Gu Kaizhi, was a famous painter in the Eastern Jin Dynasty. Emperor Chen Shubao of Chen, Emperor Ming of Tang and Emperor Huizong of Song were all talented and romantic emperors. --[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 01:02, 13 December 2021 (UTC)

==高蜜 Gāo Mì 翻译学女 202120081487==

刘庭芝即刘希夷(字庭芝)、温飞卿即温庭筠(字飞卿)，都是唐代名诗人；米南宫即米芾(南宫为世称)，是北宋名画家；石曼卿即石延年(字曼卿)、柳蓍卿即柳永(字蓍卿)、秦少游即秦观(字少游)，都是北宋著名文学家；

Liu Tingzhi, or Liu Xiyi (courtesy name Tingzhi), Wen Feiqin refers orWen Tingyun (courtesy name Feiqing) are both famous poets of the Tang Dynasty. Mi Nangong, or Mi Fu (nickname Nangong), was a famous painter of the Northern Song Dynasty; Shi Manqing, or Shi Yannian (courtesy name Manqing), Liu Yaoqing, or Liu Yong (courtesy name Yaoqing), and Qin Shaoyou, or Qin Guan (courtesy name Shaoyou), were famous literary scholars of the Northern Song Dynasty.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 01:03, 13 December 2021 (UTC)

Liu Tingzhi, or Liu Xiyi (styled Tingzhi), Wen Feiqin refers orWen Tingyun (styled Feiqing) are both famous poets of the Tang Dynasty. Mi Nangong, or Mi Fu (nickname Nangong), was a famous painter of the Northern Song Dynasty; Shi Manqing, or Shi Yannian (styled Manqing), Liu Yaoqing, or Liu Yong (styled Yaoqing), and Qin Shaoyou, or Qin Guan (styled Shaoyou), were famous literary scholars of the Northern Song Dynasty.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 12:27, 15 December 2021 (UTC)

==宫博雅 Gōng Bóyǎ 俄语语言文学女 202120081488==

倪云林即倪瓒，字云林，是元代名画家；唐伯虎即唐寅(字伯虎)、祝枝山即祝允明(字枝山)，都是明代名画家、文学家；李龟年(唐代人)、黄幡绰(唐代人)、敬新磨(五代后唐人)，都是名艺人；

Ni Yunlin, i.e Ni Zan, was a famous painter in the Yuan Dynasty. Tang Bohu i.e Tang Yin (styled Bohu), Zhu Zhishan i.e Zhu Yunming (styled Zhishan), are famous Ming dynasty painters, litterateurs; Li Gunian (Tang Dynasty), Huang Fan Chuo (Tang Dynasty), Jing Xinmo (five dynasties later Tang dynasty), are famous artists;--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 12:23, 15 December 2021 (UTC)

Ni Yunlin, or Ni Zan, or Ni Yunlin, was a famous painter in the Yuan dynasty; Tang Bohu (or Tang Yin) and Zhu Zhishan (or Zhu Yunming) were famous painters and literary figures in the Ming dynasty; Li Guinian (of the Tang dynasty), Huang Fanchuo (of the Tang dynasty), and Jing Xinmo (of the post-Tang dynasty of the Five Dynasties) were all famous artists.--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 06:39, 15 December 2021 (UTC)

==何芩 Hé Qín 翻译学女 202120081489==

卓文君(已见第一回注)、红拂(先为隋相杨素的侍女，后私奔李靖，也是前蜀·杜光庭《虬髯客传》中的女主人公)、薛涛(唐代才妓)、崔莺(即唐·元稹《会真记》、元·王实甫《西厢记》中的崔莺莺)、朝云(宋代名妓)，他们都是以才貌流芳的名女。

Zhuo Wenjun (see the first chapter note), Hong Fu (she used to be as the servant of the Sui minister Yang Su, then eloping to Li Jing; she was also the heroine of ''The Legend of the Gnarled Man'' by Du Guangting), Xue Tao (a talented prostitute of the Tang Dynasty), Cui Ying (i.e. Cui Yingying of Yuan Zhen's ''The Book of Hui Zhen'' and Wang Shifu's "The Western Chamber"), Zhaoyun (a famous prostitute of the Song Dynasty), they are all famous for their talent and beauty. --[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 06:32, 15 December 2021 (UTC)

Zhuo Wenjun ( the first chapter noted), Hong Fu (she used to be as the servant of the minister of Sui Dynasty Yang Su, then eloping to Li Jing, also the heroine of ''The Legend of the Gnarled Man'' by Du Guangting), Xue Tao (a talented prostitute of the Tang Dynasty), Cui Ying (namely Cui Yingying of Yuan Zhen's ''The Book of Hui Zhen'' and Wang Shifu's "The Western Chamber"), Zhaoyun (a famous prostitute of the Song Dynasty), they are all famous for their talent and beauty.--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 12:25, 19 December 2021 (UTC)

==胡舒情 Hú Shūqíng 英语语言文学（语言学）女 202120081490==

成则公侯败则贼──意谓成功的人便能获得公爵、侯爵之类的高官显爵，失败的人便被看作贼寇。表示世上并无公理，世人不讲是非，只论成功与失败，即只以成败论英雄。这里化用了“败则盗贼，成则帝王”。

Success makes the Duke while failure makes the theif ——which means that, If one is successful, he will be worshipped as the Duke. While one is unsuccessful, he will be despised as the thief. It expresses that there is no generally acknowledged truth in the world and people neglect justice and only pay attention to success and failure, that is, the sole measure. It coins a phrase here, “Failure makes a thief， success a king.”--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 12:25, 19 December 2021 (UTC)

The winner is Duke, the looser is theif means that the person who succeeded would be entitled like Duke and who failed would be dispised as a theif. It presents that there is no generally acknowledged truth in the world and people neglect justice and only pay attention to success and failure, that is, the sole measure. It coins a phrase here, “Failure makes a thief， success a king.”--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 14:58, 12 December 2021 (UTC)

==黄锦云 Huáng Jǐnyún 英语语言文学（语言学）女 202120081491==

出自宋·邓牧《君道》：“嘻！天下何常之有？败则盗贼，成则帝王。”东床──指女婿。典出《晋书·王羲之传》、南朝宋·刘义庆《世说新语·雅量》：晋朝太尉郗鉴派人至丞相王导家相婿，王丞相令其到东厢房随意挑选。

It is cited from Deng Mu's How to Be Emperor, a work in Song dynasty, saying "how can the world be immutable! The loser is the thief, and the winner is the emperor." Dongchuang refers to the son-in-law, used in Books of Jin: Wang Xizhi's Biography" and Liu Yiqing's "Shi Shuo Xin Yu · Elegance" (Southern Song dynasty): In Jin dynasty Tai Wei (supreme government official in charge of military affairs) Xijian sent an underlying to the prime minister Wang Dao's house for taking in a son-in-law, and Prime Minister Wang invite him to choose at will in the east wing.--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 14:43, 12 December 2021 (UTC)

It is cited from Deng Mu's How to Be Emperor, a work in Song dynasty, saying "how can the world be immutable! The loser is the thief, and the winner is the emperor." Dongchuang refers to the son-in-law, used in Books of Jin: Wang Xizhi's Biography" and Liu Yiqing's "Shi Shuo Xin Yu · Elegance" (Southern Song dynasty): In Jin dynasty Tai Wei (supreme government official in charge of military affairs) Xijian sent an official to the prime minister Wang Dao's house choosing a son-in-law, and Prime Minister Wang invited him to choose at will in the east wing room.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 14:51, 12 December 2021 (UTC)

==黄逸妍 Huáng Yìyán 外国语言学及应用语言学女 202120081492==

此人过去一看，见王家诸郎皆很矜持，唯独王羲之坦腹躺在东床之上，毫不在乎。此人回报，郗鉴即选中王羲之为婿。后世即以“东床”、“东床坦腹”、“东床客”、“东床娇客”等代指女婿。

The man looked over and saw that all the lords of Wang family were very reserved, except Wang Xizhi, who was lying on the east bed and didn't care, showing his belly. In return, Xi Jian chose Wang Xizhi as his son-in-law. Later generations referred to the son-in-law with "East Bed", "East Bed Man Showing Belly", "East Bed Guest", "East Bed Distinguished Guest" and so on.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 04:59, 12 December 2021 (UTC)

The man looked over and saw that all the lords of Wang family were very reserved, except Wang Xizhi, who was lying on the east bed and didn't care, showing his belly. In return, Xi Jian chose Wang Xizhi as his son-in-law. Later generations referred to the son-in-law with "East Bed", "East Bed Man Showing Belly", "East Bed Guest", "East Bed Distinguished Guest" and so on.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:54, 19 December 2021 (UTC)Huang Zhuliang

==黄柱梁 Huáng Zhùliáng 国别男 202120081493==

退了一舍之地──意谓退避三十里。形容退居其后，不敢与争。一舍：三十里。这里化用了“退避三舍”之典。He retreat thirty miles. It describes retreating behind and not daring to compete with. Yishe: Thirty Li. The code of "retreat and give up" is used here.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:53, 19 December 2021 (UTC)Huang Zhuliang

He retreat thirty miles. It describes retreating behind and not daring to compete with. Yishe: Thirty Li. The code of "retreat and give up" is used here
--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 12:02, 19 December 2021 (UTC)

==金晓童 Jīn Xiǎotóng 202120081494==

典出《左传·僖公二十三年》：春秋时，晋国公子重耳出奔至楚，楚成王礼遇之，因问道：“公子若反(返)晋国，则何以报不谷？”重耳对曰：“若以君之灵，得反晋国，晋、楚治兵，遇于中原，其辟(避)君三舍。”
This story comes from ''Zuo Zhuan · Xi public twenty three years'': During the Spring and Autumn Period (777-476 BC), Childe Chong Er of the state of Jin went to the state of Chu. King Cheng of Chu gave a banquet for Chong er and asked, "If childe returns to the state of Jin, how will you repay me? Chong Er answered, "If I can return to the state of Jin, if the troops of the state of Jin and the state of Chu meet each other in the Central Plains, I will ask the troops of the state of Jin to retreat 90 li.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 06:56, 12 December 2021 (UTC)

==邝艳丽 Kuàng Yànl 英语语言文学（语言学）女 202120081495==

后重耳返国为君，晋、楚城濮(在今山东省鄄城县西南)之战，重耳遵守诺言，晋军果“退三舍以辟之”。

第三回

托内兄如海荐西宾接外孙贾母惜孤女

Then Childe Chong Er came back to his country as Emperor. In the battle of Jin and Chu in Chengpu (in southwest of Juancheng county in Shandong province), he keeps his promise, then the army of Jin actually retreated to avoid the war.

Chapter 3

Entrust cousin Ru Hai with recommendations of distinguished gusts; Accept granddaughter lady Dowager takes pity on orphan girl

Then Childe Chong Er came back to his country as Emperor. In the battle of Jin and Chu in Chengpu (in southwest of Juancheng county in Shandong province), he keeps his promise, then the army of Jin actually retreated to avoid the war.

Chapter 3

Entrust cousin Ru Hai with recommendations of distinguished gusts; Welcoming her granddaughter, lady Dowager takes pity on the orphan girl.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 11:13, 20 December 2021 (UTC)

==李爱璇 Lǐ Àixuán 英语语言文学（语言学）女 202120081496==

却说雨村忙回头看时，不是别人，乃是当日同僚一案参革的张如圭。他系此地人，革后家居，今打听得都中奏准起复旧员之信，他便四下里寻情找门路，忽遇见雨村，故忙道喜。二人见了礼，张如圭便将此信告知雨村。

Yue-ts'un, turning round in a hurry, perceived that the speaker was no other than a certain Chang Ju-kuei, an old colleague of his, who had been denounced and deprived of office, on account of some case or other; a native of that district, who had, since his degradation, resided in his home.Having come to hear the news that a memorial, presented in the capital, that the former officers (who had been cashiered) should be reinstated, had received the imperial consent, he had promptly done all he could, in every nook and corner, to obtain influence, and to find the means (of righting his position,) when he, unexpectedly, came across Yue-ts'un, to whom he therefore lost no time in offering his congratulations. The two friends exchanged the conventional salutations, and Chang Ju-kuei communicated the tidings to Yue-ts'un.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 07:11, 25 December 2021 (UTC)

Yue-ts'un, speedily looking back on, perceived that the speaker was no other than a certain Chang Ju-kuei, an old colleague of his, who had participated in the former case but been denounced and deprived of office, on account of some case or other. He was a native of that district, who had resided at home since his degradation. Having lately come to hear the news that a memorial, presented in the capital, that the former officers (who had been cashiered) should be reinstated, had received the imperial consent, he had promptly done all he could to obtain influence, and to find the means of righting his position. When he, unexpectedly, came across Yue-ts'un, he offered offering his congratulations to him soon. The two friends greeted to each other, exchanging the conventional salutations, and Chang Ju-kuei forthwith passed on the information to Yue-ts'un.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 04:55, 15 December 2021 (UTC)

==李瑞洋 Lǐ Ruìyáng 英语语言文学（英美文学）女 202120081497==

雨村欢喜，忙忙叙了两句，各自别去回家。冷子兴听得此言，便忙献计，令雨村央求林如海，转向都中去央烦贾政。雨村领其意而别，回至馆中，忙寻邸报看真确了。次日，面谋之如海。如海道：“天缘凑巧。

Yue-ts'un was delighted, but after he had made a few remarks in a hurry, each took his leave and sped on his own way homewards. After hearing this conversation, Leng Tzu-hsing hastened at once to propose a plan, advising Yue-ts'un to request Lin Ju-hai, then, in his turn, to appeal to Chia Cheng in the capital for support. Yue-ts'un accepted the suggestion, and took leave of him. Upon returning to the quarter, he made all haste to lay his hand on the Metropolitan Gazette, to ascertain whether the news was authentic or not. On the next day, he had a personal consultation with Ju-hai. "Providence and good fortune are both alike propitious!" said by Ju-hai.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 04:57, 15 December 2021 (UTC)

Yue-ts'un was delighted, but after he they made a short conversation, each of them stepped on their own way homewards. After hearing the words of Yue-ts'un, Leng Tzu-hsing hastened at once to propose a plan, advising Yue-ts'un to request Lin Ju-hai, then, in his turn, to appeal to Chia Cheng in the capital for support. Yue-ts'un accepted the suggestion, and took leave of him. Upon returning to the quarter, he made all haste to read the Metropolitan Gazette, to ascertain the authenticity of that news. On the next day, he made a personal consultation with Ju-hai. Thus, Ju-hai said, "Providence and good fortune are both alike propitious!" --[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 13:06, 15 December 2021 (UTC)

==李姗 Lǐ Shān 英语语言文学（英美文学）女 202120081498==

因贱荆去世，都中家岳母念及小女无人依傍，前已遣了男女、船只来接，因小女未曾大痊，故尚未行。此刻正思送女进京。因向蒙教训之恩，未经酬报，遇此机会，岂有不尽心图报之理？弟已预筹之，修下荐书一封，托内兄务为周全，方可稍尽弟之鄙诚；

Since my wife has passed away, my mother-in-law has long before dispatched servants and transporting boats here to fetch my lonely daughter. But she has not set off yet due to the fact that she had not fully recovered at that time. As she is in good condition now, I am considering sending her to her grandma's. Once you have taught my daughter but desired no handsome payment; while now you need help, how can I sit on the fence? I have already well prepared for that in advance --- a recommendation letter has been written to my brother-in-law, to ensure your success in career. Only in this way can I show my gratitude towards you.--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 08:15, 11 December 2021 (UTC)

Since my wife has passed away, my mother-in-law who lives in the capital worried that my daughter has no one to rely on. So she has long before dispatched servants and transporting boats here to fetch my lonely daughter. But she has not set off yet due to the fact that she had not fully recovered at that time. As she is in good condition now, I am considering sending her to her grandma's. Once you have taught my daughter but desired no handsome payment; while now you need help, how can I sit on the fence? I have already well prepared for that in advance --- a recommendation letter has been written to my brother-in-law, to ensure your success in career. Only in this way can I show my gratitude towards you.--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 07:43, 12 December 2021 (UTC)

==李双 Lǐ Shuāng 翻译学女 202120081499==

即有所费，弟于内家信中写明，不劳吾兄多虑。”雨村一面打恭，谢不释口；一面又问：“不知令亲大人现居何职？只怕晚生草率，不敢进谒。”如海笑道：“若论舍亲，与尊兄犹系一家，乃荣公之孙：大内兄现袭一等将军之职，名赦，字恩侯；

“As for the possible costs, I will explain in the letter. You don’t need to worry about it.” Yu Cun bent down and expressed his gratitude, asking: “What does your brother do now? I’m worried that I would take the liberty to pay a visit, it’s too hasty.” Ru Hai laughed and said: “My brother and your brother belong to the same family. They are both descendants of Origin Merchant. My eldest brother is now a first-class general, his name is Pardon Merchant, whose alternative given name is Enhou.”--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 07:38, 12 December 2021 (UTC)

“As for the possible costs, I will explain in the letter. You needn’t to worry about it.” Yu Cun bent down and expressed his gratitude, asking: “What does your brother do now? I’m worried that I would take the liberty to pay a visit, it’s too hasty.” Ru Hai laughed and said: “My brother and your brother belong to the same family. They are both descendants of Ronggong. The eldest brother of my wife is now a first-class general, his name is Pardon Merchant, whose alternative given name is Enhou.” --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 23:46, 12 December 2021 (UTC)

==李文璇 Lǐ Wénxuán 英语语言文学（英美文学）女 202120081500==

二内兄名政，字存周，现任工部员外郎，其为人谦恭厚道，大有祖父遗风，非膏粱轻薄之流，故弟致书烦托，否则不但有污尊兄清操，即弟亦不屑为矣。”雨村听了，心下方信了昨日子兴之言，于是又谢了林如海。

“The second brother of my wife named Zheng, his style name is Cunzhou. He is the Yuanwai official of the Ministry of Works in feudal China. He is moderate and kind, has the dignity of his grandfather, and is not the flimsy type. Therefore, my brother sent a letter to me. Otherwise, I will not only pollute my brother's operation, but also despise my brother.” After hearing this, Yuchun had believed the words of Zixing yesterday, therefore, he thanked Lin Ruhai again. --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 01:27, 12 December 2021 (UTC)

The second brother-in-law is named Zheng, and the word is kept in Zhou. He is currently a member of the Ministry of Engineering. He is courteous and kind. He has a grandfather's legacy. He is not anointing and frivolous. Disdainful. "Yucun listened, and believed in Xing's words from yesterday, so he thanked Lin Ruhai again.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 14:12, 12 December 2021 (UTC)

==李雯 Lǐ Wén 英语语言文学（英美文学）女 202120081501==

如海又说：“择了出月初二日小女入都，吾兄即同路而往，岂不两便？”雨村唯唯听命，心中十分得意。如海遂打点礼物并饯行之事，雨村一一领了。那女学生原不忍离亲而去，无奈他外祖母必欲其往，且兼如海说：“汝父年已半百，再无续室之意；
Ruhai also said: "I chose the girl to enter the capital on the second day of the lunar month, and my brother will go the same way. Isn't it both convenient?" Yucun obeyed,and RuHai was very satisfied . Ruhai then took some gifts and walked away, and Yucun took them one by one. The girl student couldn't bear to leave her relatives, but his grandmother wanted to go there. She also said like the sea: "Your father is half a hundred years old, and there is no intention to remarry.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 14:11, 12 December 2021 (UTC)
Ruhai said, "I chose the second day of the month to enter the capital, and my brother went the same way. Rain village obedient, the heart is very proud. Such as Haisui make gifts and farewell dinner, Rain village one by one. The girl could not bear to leave her, but her grandmother wanted her to go, saying, "Your father is fifty years old, and has no intention of staying in the house;--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 12:27, 19 December 2021 (UTC)

==李新星 Lǐ Xīnxīng 亚非语言文学女 202120081503==

且汝多病，年又极小，上无亲母教养，下无姊妹扶持。今去依傍外祖母及舅氏姊妹，正好减我内顾之忧，如何不去？”黛玉听了，方洒泪拜别，随了奶娘及荣府中几个老妇登舟而去。雨村另有船只，带了两个小童，依附黛玉而行。
You are sick, you are young, you have no mother to nurse you, and no sisters to nurse you. Now I am going to my grandmother and my uncle and sisters, which will relieve my worries. Why not?" When Daiyu heard this, she said goodbye with tears and followed the wet nurse and some old women in the Rong House to the boat. Yucun had another boat with two children attached to Daiyu.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 12:25, 19 December 2021 (UTC)

And you are sick, very young, no mother to raise, no sister support. Today I go to rely on my grandmother and uncle's sisters, just to reduce my internal worries, how not to go? Dai Yu listened, and Fang shed tears to say goodbye, and followed the grandmother and several old women in the Rong Mansion to board the boat. There was another boat in the rain village, with two children, who were attached to Daiyu.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 12:29, 19 December 2021 (UTC)

==李怡 Lǐ Yí 法语语言文学女 202120081504==

一日到了京都，雨村先整了衣冠，带着童仆，拿了宗侄的名帖，至荣府门上投了。彼时贾政已看了妹丈之书，即忙请入相会。见雨村相貌魁伟，言谈不俗；且这贾政最喜的是读书人，礼贤下士，拯溺救危，大有祖风；况又系妹丈致意：因此优待雨村，更又不同。
One day, when YuCun arrived in Jingdou, he dressed himself, and went to Rongfu with his nephew's name card. At this time Master Jia had seen his brother-in-law's letter, immediately invited him to come in to meet. Yucun looked tall and handsome and talked well. And Master Jia most like scholar, courtesy, saving, great predecessors style; Therefore, Master Jia is very good to Yucun. He is different from others.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 08:18, 11 December 2021 (UTC)

One day, when YuCun arrived in Jingdou, he dressed himself, and went to Rongfu with his nephew's name card. At the very moment that Master Jia had received his brother-in-law's letter, he immediately invited him to come in to meet. Yucun looked tall and handsome and talked well. And Master Jia most like scholar, courtesy, saving, great predecessors style; Therefore, Master Jia is very good to Yucun. He is different from others--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 12:39, 19 December 2021 (UTC)

==刘沛婷 Liú Pèitíng 英语语言文学（英美文学）女 202120081505==

便极力帮助，题奏之日，谋了一个复职。不上两月，便选了金陵应天府，辞了贾政，择日到任去了，不在话下。且说黛玉自那日弃舟登岸时，便有荣府打发轿子并拉行李车辆伺候。这黛玉尝听得母亲说，他外祖母家与别人家不同

They tried to help, the day of the title, sought a reinstatement. Within two months, he was elected to Jinling Yingtianfu, resigned from Jia Zheng, and left for his post on a certain day. Now, when Daiyu abandoned her boat and landed on the shore that day, she was served by a sedan chair sent by the Rongfu and a luggage cart. Daiyu heard from her mother that her grandmother's family was different from others.--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 12:40, 19 December 2021 (UTC)

They sought to a position the day that he presented a petition to the throne. Within two months, he was elected to Jinling Mansion, resigned from Master Merchant，and left for his post on a certain day. Now, when Daiyu disembarked that day, she was served by a sedan chair sent by the Rongguo Mansion and a luggage cart. Daiyu heard from her mother that her grandmother's family was different from others.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 12:44, 19 December 2021 (UTC)

==刘胜楠 Liú Shèngnán 翻译学女 202120081506==

他近日所见的这几个三等的仆妇，吃穿用度，已是不凡；何况今至其家，都要步步留心，时时在意，不要多说一句话，不可多行一步路，恐被人耻笑了去。自上了轿，进了城，从纱窗中瞧了一瞧，其街市之繁华，人烟之阜盛，自非别处可比。

In the past few days, she has been deeply impressed by the food, clothing and behavior of the low- ranking attendants who accompanied her. She decided that in their new home, she must always be vigilant and carefully weigh every word so as not to be ridiculed for any stupid mistake. When she carried into the city, she peeped out through the gauze window on her chair at the bustling and crowded streets, which she had never seen before.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 08:32, 11 December 2021 (UTC)

The three-class servants she had seen recently have an extraordinary cost of food and clothing. What's more, since got on the sedan chair and entered the city, the prosperous market and the populousness of the city through the screen window were not comparable to other places. when coming to grandmother's mansion must pay attention to every step and be cautious with words so as not to be ridiculed by others. Daiyu thought. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 15:56, 12 December 2021 (UTC)Liu Wei

==刘薇 Liú Wēi 国别女 202120081507==

又行了半日，忽见街北蹲着两个大石狮子，三间兽头大门，门前列坐着十来个华冠丽服之人。正门不开，只东、西两角门有人出入。正门之上有一匾，匾上大书“敕造宁国府”五个大字。黛玉想道：“这是外祖的长房了。”

After half day, there are two large stone lions squatting on the north side of the street, three gates decorated with beast head, and a dozen people in gorgeous crowns and clothes are sitting in front of the gate. The main gate is closing, only the east and west corners enterences are accessible. There is a plaque above the main gate with five big characters "Ningguo Mansion". "That must be grandfather's the first son's mansion."Daiyu thought. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 15:39, 12 December 2021 (UTC)Liu Wei

After another half-day walk, they came to a street with two huge stone lions crouching on the north side and three gates decorated with beast head, in front of which ten or more people in gorgeous crowns and clothes were sitting. The main gate was shut, with only people passing in and out of the other two smaller gates. On a board above the main gate was written in big characters "Ningguo Mansion Built at Imperial Command". Daiyu realized that this must be where the elder branch of her grandmather's family lived.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 05:40, 13 December 2021 (UTC)

==刘晓 Liú Xiǎo 英语语言文学（英美文学）女 202120081508==

又往西不远，照样也是三间大门，方是荣国府，却不进正门，只由西角门而进。轿子抬着走了一箭之远，将转弯时便歇了轿，后面的婆子也都下来了。另换了四个眉目秀洁的十七八岁的小厮上来抬着轿子，众婆子步下跟随。

A little further to the west they came to another three gates. This was the Rong Mansion. Instead of going through the main gate, they entered the one on the west. The bearers carried the chair a bow-shot further, and then set it down at the turning and withdrew, the maidservants now going down the chair. Another four seventeen or eighteen smartly dressed lads picked up the chair, followed by the maids.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 05:09, 12 December 2021 (UTC)

Not far to the west is the same three-room gate, which is the Rongguo Mansion. Instead of going through the main gate, they entered the one on the west. The bearers carried the chair a bow-shot further, and then set it down at the turning and withdrew, the maidservants now going down the chair. Another four seventeen or eighteen smartly dressed lads picked up the chair, followed by the maids.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 07:26, 12 December 2021 (UTC)

==刘越 Liú Yuè 亚非语言文学女 202120081509==

至一垂花门前落下，那小厮俱肃然退出。众婆子上前打起轿帘，扶黛玉下了轿。黛玉扶着婆子的手，进了垂花门，两边是超手游廊，正中是穿堂，当地放着一个紫檀架子大理石屏风。转过屏风，小小三间厅房。

When the palanquin was dropped in front of a pendant door, the attendants all retired in silence. The ladies came forward and raised the curtain of the palanquin and helped Daiyu out of the palanquin. The two sides of the door are overhand corridors, and the centre is a hall with a marble screen on a rosewood frame. Turning past the screen, there is a small three-room hall.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 07:22, 12 December 2021 (UTC)

After the palanquin was dropped in front of a floral-pendant gates, the attendants all retreated in silence. The maids came forward and drew the curtain of the palanquin to help Mascara Jade Forest out of the palanquin. Holding the hands of those maids, Black Jade enter the floral-pendant gates. On the two sides of the door were Chaoshou veranda, and in the center was a vestibule with a marble screen in a rosewood frame. Past the screen, there were three small rooms. --[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 13:01, 19 December 2021 (UTC)

==刘运心 Liú Yùnxīn 英语语言文学（英美文学）女 202120081510==

厅后便是正房大院：正面五间上房，皆是雕梁画栋；两边穿山游廊、厢房，挂着各色鹦鹉、画眉等雀鸟。台阶上坐着几个穿红着绿的丫头，一见他们来了，都笑迎上来道：“刚才老太太还念诵呢，可巧就来了。”于是三四人争着打帘子。一面听得人说：“林姑娘来了。”

Behind the banqueting hall was the courtyard of the principal rooms: the five principal rooms on the front all had carved beams and painted rafters; from the roof of the verandah on both sides, the cages of parrots, thrushes and various birds hung there. A few girls in red and green sat on the steps. Saw they coming, the girls all smiled and came up: “Just now grandma was taking about you. You arrived just in time.” Then they rushed to pull the curtain. From the other side, a man said: “Miss Forest is coming.”--[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:28, 19 December 2021 (UTC)

Behind the hall was the courtyard of the central house: five principal rooms in the front with carved beams, while along two sides corridors and chambers with colorfully painted birds as parrots and thrush. There were several maids in red and green sitting on the steps. Seeing visitors coming, they greeted them with smiles, saying, "The old lady just talked about you again and again in anticipation, and here you are." then the four maids scrambled to open the curtain. Meanwhile a man said, "Miss Lin is coming."--[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 12:47, 19 December 2021 (UTC)

==罗安怡 Luó Ānyí 英语语言文学（英美文学）女 202120081511==

黛玉方进房，只见两个人扶着一位鬓发如银的老母迎上来。黛玉知是外祖母了，正欲下拜，早被外祖母抱住，搂入怀中，“心肝儿肉”叫着大哭起来。当下侍立之人无不下泪，黛玉也哭个不休。众人慢慢解劝，那黛玉方拜见了外祖母。
An silver-haired old lady supported by two maids came and welcomed her while Black Jade entered the room. Realizing that this was her grandmother, Black Jade was about to bow down to show her respects. Suddenly she was tightly hugged by grandmoa who crying out harrowingly "my sweet heart!" Servants and maids were all in tears, and Black Jade also sobbed unceasingly. People persuaded them softly, then Black Jade was able to pay her respects to her grandmother. --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 12:14, 19 December 2021 (U

As Dai Yu just came to the home, there came a silver-haired old woman.Dai Yu knew she was grandma, and as she was going to bow down to show her respect, she has been already hugged by her grandma, who cried:"my sweety!". The surrounding maids all cried, as well as Dai Yu. The crowds slowy persuade her, and Dai Yu then showed her respect to her grandma.--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 14:01, 19 December 2021 (UTC)

==罗曦 Luó Xī 英语语言文学（英美文学）女 202120081512==

贾母方一一指与黛玉道：“这是你大舅母。这是二舅母。这是你先前珠大哥的媳妇珠大嫂子。”黛玉一一拜见。贾母又说：“请姑娘们。今日远客来了，可以不必上学去。”众人答应了一声，便去了两个。

Baoyu's grandmother than introduce them respectively:"This is your eldest aunt, and this is your second aunt.This is your Zhu brother's wife. Dai Yu greet them one by one.Baoyu's grandmother than said that:"Invite the gilrs. Today here come the dear guest, so they don't need to go to school." Surrounding people said yes, and two of them left.

The Lady Dowager then introduced them respectively to Daiyu: "This is your eldest aunt, and this is your second uncle's wife. This is your deceased elder brother Zhu's wife." Daiyu greeted them one by one. Her grandmother then said: "Tell all the girls to come here. We have visitor who came from afar, so they don't need to go to school." Surrounding people answered yes, and two of them left to call them.--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 07:22, 20 December 2021 (UTC)

==马新 Mǎ Xīn 外国语言学及应用语言学女 202120081513==

不一时，只见三个奶妈并五六个丫鬟，拥着三位姑娘来了：第一个肌肤微丰，身材合中，腮凝新荔，鼻腻鹅脂，温柔沉默，观之可亲；第二个削肩细腰，长挑身材，鸭蛋脸儿，俊眼修眉，顾盼神飞，文彩精华，见之忘俗；

In a little while, three grannies and five or six servant girls turned up, clustering with three ladies. The first was somewhere plump in figure and of average height; her cheek was in beautiful shape, like a fresh lichee; her nose was glossy like the goose grease; she was gentle and quiet in nature, who looks very friendly. The second was thin and tall with an oval face, sparking eyes and long eyebrows; her elegance and quick-witted mind tickle people’s fancy, letting them forget everything vulgar.--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 08:11, 11 December 2021 (UTC)

After a while, the three young ladies showed up, escorted by three wet nurses and five or six maids. The first was slightly plump and of medium height; her cheeks were as smooth and soft as the newly ripened lichees, and her nose was as glossy as goose fat. She was tender and reticent, and looked very affable. The second had drooping shoulders and a slender waist; she was tall and slim, with an oval face, bright and piercing eyes as well as delicate eyebrows. She seemed elegant, quick-witted and in high spirits, with a display of distinctive charm. People who looked at her were to forget everything vulgar and tawdry.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 23:42, 11 December 2021 (UTC)

==毛雅文 Máo Yǎwén 英语语言文学（英美文学）女 202120081514==

第三个身量未足，形容尚小：其钗环裙袄，三人皆是一样的妆束。黛玉忙起身，迎上来见礼，互相厮认，归了坐位。丫鬟送上茶来。不过叙些黛玉之母如何得病，如何请医服药，如何送死发丧。不免贾母又伤感起来，因说：“我这些女孩儿，所疼的独有你母亲。

The third one was not yet fully grown, and she still had the face of a child. All the three young ladies were dressed in similar garments, that is, the tunics and the skirts with the same bracelets and head ornaments. Daiyu hastily rose to greet politely these cousins, and then they introduced to and acquainted with each other, after which they took seats while the maids served the tea. All their talk now was about Daiyu's mother: the culprit for her illness, the medicine that the doctors prescribed for treating her disease, and the conduction of her funeral and mourning ceremonies. Inevitably, the Lady Dowager couldn't help being affected painfully. "Of all my chilren I loved your mother best," she told Daiyu.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 07:49, 11 December 2021 (UTC)

==毛优 Máo Yōu 俄语语言文学女 202120081515==

今一旦先我而亡，不得见面，怎不伤心！”说着，携了黛玉的手，又哭起来。众人都忙相劝慰，方略略止住。众人见黛玉年纪虽小，其举止言谈不俗；身体面貌虽弱不胜衣，却有一段风流态度，便知他有不足之症。

Once she died before me, I could not see her again. She said, taking Mascara Jade Forest's hand, and cried again. Everyone was busy trying to console her, and soon she slightly stopped. They saw that although Mascara Jade Forest was young, her manner and speech were not ordinary; although her health was weak, she had graceful and elegant manner, so they knew that she had a disease of deficiency.--[[User:Mao You|Mao You]] ([[User talk:Mao You|talk]]) 08:43, 11 December 2021 (UTC)

"Once she died before me, it is so sad that I could not see her again." she said, taking Mascara Jade Forest's hand, and cried again. Everyone was trying to console her, and then she slightly stopped. They saw that although Mascara Jade Forest was young, her manner and speech were not ordinary; although she was weak, she had graceful and elegant gestures, so they learned that she had a disease of deficiency.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 06:35, 12 December 2021 (UTC)

==牟一心 Móu Yīxīn 英语语言文学（英美文学）女 202120081516==

因问：“常服何药？为何不治好了？”黛玉道：“我自来如此，从会吃饭时便吃药到如今了，经过多少名医，总未见效。那一年我才三岁，记得来了一个癞头和尚，说要化我去出家，我父母自是不从。

So they asked:" What medicine do you usually take? Why doesn't it work?" Mascara Jade Forest replied:" I am used to getting along with my disease. I have been taking medicine since I could eat. A lot of famous daocters cannot contribute to my illness.When I was three years old, a monk with favus on the head came to persuade me to become a nun,but my parents declined him.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 08:07, 11 December 2021 (UTC)

They then asked, "What medicines do you take regularly? Why can't you cure your illness?" Mascara Jade Forest, "I am used to getting along with my disease. I have been taking medicine since I could eat. A lot of famous docters cannot contribute to my illness. I was only three years old when I remember a mangy monk came and said he wanted to convert me to a monk, but my parents refused.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 06:29, 13 December 2021 (UTC)

==彭瑞雪 Péng Ruìxuě 法语语言文学女 202120081517==

他又说：‘既舍不得他，但只怕他的病，一生也不能好的；若要好时，除非从此以后，总不许见哭声，除父母之外，凡有外亲，一概不见，方可平安了此一生。’这和尚疯疯癫癫，说了这些不经之谈，也没人理他。

The monk said, "if you can't bear to part with her she'll probably nerver get well. The only remedy is to keep her from hearing weeping and from seeing any relatives apart from her father and mother. That's her only hope of having a quiet life." No one paid any attention, of course, to such crazy talk.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 06:24, 13 December 2021 (UTC)

The monk said, "if you can't bear to separate with her, she'll probably nerver get well. The only remedy is to keep her from hearing weeping and from seeing any relatives apart from her father and mother. That's her only hope of having a quiet life." No one paid any attention, of course, to such nonsense talk.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 12:12, 19 December 2021 (UTC)

[[Media:Example.ogg]]==秦建安 Qín Jiànān 外国语言学及应用语言学女 202120081518==

如今还是吃人参养荣丸。”贾母道：“这正好，我这里正配丸药呢，叫他们多配一料就是了。”一语未完，只听后院中有笑语声，说：“我来迟了，没得迎接远客。”黛玉思忖道：“这些人个个皆敛声屏气如此，这来者是谁，这样放诞无礼？”

Now Mascara Jade Forest is still taking ginseng pills.And Grandma Merchant said:" What a coincidence! The pills are making now, I just tell them to add one." The words have not been finished, but there is a laugh in the back yard, which said:" I come late and fail to welcome our distinguished guest." Mascara Jade Forest thought: all people here are holding their breath, who is this person that is so arrogant and rude?--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 08:19, 11 December 2021 (UTC)

Now Lin Daiyu is still taking ginseng pills. And Grandma Merchant said:" It just so happens that I have been asking them to dispense the pills, just asking them to do one more portion." The words are not finished, but there is a laugh in the back yard, which said:" I am late and fail to welcome our distinguished guest." Mascara Jade Forest thought: “all people here are holding their breath, who is this person that is so arrogant and rude?”--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 09:33, 12 December 2021 (UTC)

==邱婷婷 Qiū Tíngtíng 英语语言文学（语言学）女 202120081519==

心下想时，只见一群媳妇、丫鬟拥着一个丽人，从后房进来。这个人打扮与姑娘们不同，彩绣辉煌，恍若神妃仙子：头上戴着金丝八宝攒珠髻，绾着朝阳五凤挂珠钗；项上戴着赤金盘螭缨络圈；身上穿着缕金百蝶穿花大红云缎窄褃袄，外罩五彩刻丝石青银鼠褂；

While Mascara Jade Forest is still thinking about it, a group of daughters-in-law and maids cluster around a beauty coming in from the back room. She dresses up differently from other girls, with colorful embroidery splendor, and looks like a divine concubine or a fairy: wearing a gold silk beads bun decorated with eight treasures and the five phoenix hairpin hanging with beads on the head; a red gold coiled chi dragon tassel ring around the neck; the bright red made of cloud satin material narrow lining cotton jacket with decorations of wisps of gold hundred butterflies and flowers, and the outer coat with decorations of the multicolored engraved silk stone green silver mouse. --[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 09:34, 12 December 2021 (UTC)

Mascara Jade Forest was still thinking about it when she saw a group of daughters-in-law and maids embracing a beautiful woman who came in from the back room. This woman dresses differently from the girls, with colorful embroidery splendor, and looks like a divine concubine fairy: wearing a gold silk eight treasure save beads bun and the sunrise five phoenix hanging beads hairpin on the head; a red gold coiled chi dragon tassel ring around the neck; wearing the bright red made of cloud satin material narrow lining cotton jacket with decorations of wisps of gold hundred butterflies and flowers, and the outer coat with decorations of the multicolored engraved silk stone green silver mouse.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 07:47, 11 December 2021 (UTC)

==饶金盈 Ráo Jīnyíng 英语语言文学（语言学）女 202120081520==

下着翡翠撒花洋绉裙。一双丹凤三角眼，两弯柳叶吊梢眉。身量苗条，体格风骚。粉面含春威不露，丹唇未启笑先闻。黛玉连忙起身接见。贾母笑道：“你不认得他。他是我们这里有名的一个泼辣货，南京所谓‘辣子’，你只叫他‘凤辣子’就是了。”

Splendid Pheonix King wore a jadeite flowered dress underneath, with a pair of phoenix triangle eyes and two curved willow hanging eyebrows. Her figure is slim and her physique is flirtatious. She can be described with “ the face is delicate and beautiful, spirited character of her is not revealed in the appearance, red lips beautiful, not yet open mouth first heard her laugh”. Mascara Jade Forest hastily got up to curtsy to her. Grandma Merchant said with a smile, "You do not recognize her. She is famous for her boldness and vigorousness here, she is truly the 'chilli woman' in Nanjing dialect, you can just call her ' chilli Feng'."--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 07:35, 11 December 2021 (UTC)

Splendid Pheonix King, characterized by a pair of phoenix triangle eyes and two curved willow hanging eyebrows, wore an emerald flowered crepe skirt. She was slender and coquettish, with a delicate face and a smiling lip. Mascara Jade Forest promptly rose quickly to greet her. Grandma Merchant said with a smile: “ you don’t know him. He is famous for her fierceness and toughness, namely the so-called Nanjing chilli. So you can just call him ‘Chilli Pheonix’.”--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 12:48, 11 December 2021 (UTC)

==石丽青 Shí Lìqīng 英语语言文学（英美文学）女 202120081521==

黛玉正不知以何称呼，众姊妹都忙告诉黛玉道：“这是琏二嫂子。”黛玉虽不曾识面，听见他母亲说过：大舅贾赦之子贾琏，娶的就是二舅母王氏的内侄女，自幼假充男儿教养，叫做王熙凤学名。黛玉忙陪笑见礼，以“嫂”呼之。

Mascara Jade Forest was insensible of what to call her. Then her sisters told her promptly: “ this is your sister-in-law Romance Second Merchant.” Although Mascara Jade Forest had never met her, she heard of her from his mother: Romance Merchant, the son of her Uncle Pardon Merchant, had married the niece of Aunt King, named scientifically Splendid Phoenix King, was brought up as a male offspring since childhood. Mascara Jade Forest was engaged in smiling and saluting at her, calling her “sister-in-law”.--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 12:32, 11 December 2021 (UTC)

Daiyu didn't know what to call her. Then her sisters told her promptly: “This is your sister-in-law Lian Er.” Although Daiyu had never met her, she heard of her from his mother: Jia Lian, the son of her Uncle Jia She, had married the niece of Aunt Wang.She was brought up as a male offspring since childhood and her academic name is Wang Xifeng. Daiyu was engaged in smiling and saluting at her, calling her “sister-in-law”.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 01:55, 13 December 2021 (UTC)

==孙雅诗 Sūn Yǎshī 外国语言学及应用语言学女 202120081522==

这熙凤携着黛玉的手，上下细细打量了一回，便仍送至贾母身边坐下，因笑道：“天下真有这样标致人儿！我今日才算看见了。况且这通身的气派，竟不像老祖宗的外孙女儿，竟是嫡亲的孙女儿似的，怨不得老祖宗天天嘴里心里放不下。

Taking Daiyu's hand, Xifeng looked up and down her carefully, then she sent her to Mother Jia's side to sit down.She laughed and said:"There is really such a beautiful person in the world!I didn't see her until today.Moreover,the style of her makes her be more like your son's daughter than your daughter's daughter.It's no wonder that you are concerned about her so much.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 01:49, 13 December 2021 (UTC)

Taking Mascara Jade Forest's hand, Splendid Phoenix King looked her up and down carefully, then sent her to Grandma Merchant's side to sit down. She laughed and said:"There is really such a beautiful person in the world! I haven’t seen her until today. Moreover, her extraordinary temperament makes her be more like your son's daughter rather than your daughter's daughter. It's no wonder that you are concerned about her so much. --[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 06:48, 13 December 2021 (UTC)

==王李菲 Wáng Lǐfēi 英语语言文学（英美文学）女 202120081523==

只可怜我这妹妹这么命苦，怎么姑妈偏就去世了呢？”说着便用帕拭泪。贾母笑道：“我才好了，你又来招我；你妹妹远路才来，身子又弱，也才劝住了：快别再提了。”

I pity my sister for being so miserable, how could my aunt died so early?" She said, wiping her tears with her handkerchief. Grandma Merchant laughed and said, "I've just recovered. You come to provoke me again. Your sister has just arrived from a long journey and is weak, so she has just been persuaded: Don't mention it again."--[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 02:37, 12 December 2021 (UTC)

I pity my sister who is so miserable, how could my aunt have died?" She said, wiping her tears with her handkerchief. Your sister has only just arrived from a long journey and is weak, so she has only just been persuaded to stop talking about it."--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 08:22, 11 December 2021 (UTC)

==王逸凡 Wáng Yìfán 亚非语言文学女 202120081524==

熙凤听了，忙转悲为喜道：“正是呢，我一见了妹妹，一心都在他身上，又是喜欢，又是伤心，竟忘了老祖宗了。该打，该打！”又忙拉着黛玉的手问道：“妹妹几岁了？可也上过学？现吃什么药？在这里别想家。

The first time I saw my sister, I was all over him, and I liked him, and I was sad, and I forgot about my ancestors. You should be beaten, you should be beaten!" He also took Daiyu's hand and asked, "How old is my sister? How old is she? What kind of medicine do you take now? Don't be homesick here.--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 08:21, 11 December 2021 (UTC)

The first time I saw my sister, I was all over him, and I liked him, and I was sad, and I forgot about my ancestors. You should be beaten, you should be beaten!" He also took Daiyu's hand and asked, "How old is my sister? How old is she? What kind of medicine do you take now? Don't be homesick here.--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 11:14, 22 December 2021 (UTC)

==王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525==

要什么吃的，什么玩的，只管告诉我；丫头、老婆们不好，也只管告诉我。”黛玉一一答应。一面熙凤又问人：“林姑娘的东西可搬进来了？带了几个人来？你们赶早打扫两间屋子，叫他们歇歇儿去。”

Just tell me what you want to eat and play; Girls and old servants are not good, just tell me. " Daiyu nodded one by one. On one side, Xifeng asked, "have you moved in Miss Lin's things? How many people have you brought? Clean the two rooms early and tell them to have a rest."--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 06:54, 12 December 2021 (UTC)

Tell me what you want to eat and play; And if the maids or old nurses aren't good to you, just let me know. " Mascara Jade Forest nodded one by one. At the same time, Splendid Phoenix asked, "Have Miss Forest's things been moved in? And how many people does she bring? Clean the two rooms as soon as possible and tell them to have a rest there."--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 08:24, 12 December 2021 (UTC)

==卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526==

说话时已摆了果茶上来，熙凤亲自布让。又见二舅母问他：“月钱放完了没有？”熙凤道：“放完了。刚才带了人到后楼上找缎子，找了半日，也没见昨儿太太说的那个。想必太太记错了。”王夫人道：“有没有，什么要紧！”

Fruits and tea had been prepared when Xifeng was talking, and she arranged them by herself. The second aunt asked her whether the monthly payment has been given out, she answered yes. “I looked for the satin in the back stairs with some people for hours just now, but didn’t find which madam mentioned yesterday. Madam must be wrong.” Wang Xifeng said, and Mrs. Wang answered, “ It doesn’t matter if there is or not.”--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 07:45, 12 December 2021 (UTC)

Fruits and tea had been prepared when Xifeng was talking, and she arranged them by herself. The second aunt asked her, "Have the monthly payment been given out?" Xifeng answered, "Yes. And I looked for the satin in the back stairs with some people for hours just now, but didn’t find what madam mentioned yesterday. Madam mabey remember something wrong.” Mrs. Wang replied, “ It doesn’t matter if there is or not.”--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 09:03, 12 December 2021 (UTC)

==魏楚璇 Wèi Chǔxuán 英语语言文学（英美文学）女 202120081527==

因又说道：“该随手拿出两个来，给你这妹妹裁衣裳啊。等晚上想着，再叫人去拿罢。”熙凤道：“我倒先料着了，知道妹妹这两日必到，我已经预备下了。等太太回去过了目，好送来。”

Mrs. Wang said, "You should take out a couple of satin pieces to cut your sister's dress. When you think of this matter in the evening, send someone for the satin ." Xifeng said, "I expected it. I knew my sister would arrive in these two days, and I had already made preparations. I will send someone for the satin as soon as you have returned and examined it."--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 08:52, 12 December 2021 (UTC)

Mrs. Wang added, "You should take out a couple of satin pieces to cut your sister's dress. When you think of this in the evening, send someone for the satin ." Xifeng said, "I have expected it. I know my sister will arrive in these two days, and I have already made preparations. I will send someone for the satin as soon as you have examined it."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 13:58, 12 December 2021 (UTC)

==魏兆妍 Wèi Zhàoyán 英语语言文学（英美文学）女 202120081528==

王夫人一笑，点头不语。当下茶果已撤，贾母命两个老嬷嬷带黛玉去见两个舅舅去。维时贾赦之妻邢氏忙起身笑回道：“我带了外甥女儿过去，到底便宜些。”

Her Ladyship smiled, nodded and said nothing. Now the refreshments were cleared away and the Lady Dowager ordered two nurses to take Daiyu to see her two uncles. At this time, Mrs. She also immediately stood up, replied with smile, "it's also very convenient for me to take my niece."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 13:51, 11 December 2021 (UTC)

Her Ladyship smiled, nodded but said nothing. Now the refreshments were cleared away and the Lady Dowager ordered two mothers to take Daiyu to see her two uncles. At this time, Mrs. She immediately stood up, replied with a smile, "it's also very convenient for me to take my niece."--[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 08:37, 12 December 2021 (UTC)

==吴婧悦 Wú Jìngyuè 俄语语言文学女 202120081529==

贾母笑道：“正是呢，你也去罢，不必过来了。”那邢夫人答应了，遂带着黛玉，和王夫人作辞，大家送至穿堂。垂花门前早有众小厮拉过一辆翠幄青油车来，邢夫人携了黛玉坐上，众老婆们放下车帘，方命小厮们抬起。

Jiamu laughed and said: “ Yeah, you can also leave, and don’t have to come here.” Ms. Xing promised, and said goodbye to Ms Wang with Daiyu, all of them went through the hallway. The ingenious green carriage, which drove by a group of manservants stood in front of the floral-pendant gates, Ms. Xing set in the car with Daiyu, several old mothers put down the car shade, instructing boys uplift the carriage. --[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 08:35, 12 December 2021 (UTC)
The mother laughed and said, "Exactly, you also go, no need to come." That Mrs. Xing agreed, so took Daiyu, and Mrs. Wang to say goodbye, we sent to the wear hall. The tent green oil carriage in front of the flower gate, Mrs. Xing took Daiyu to sit on it, the wives put down the curtain, and ordered the boys to lift it.--[[User:Wu Yinghong|Wu Yinghong]] ([[User talk:Wu Yinghong|talk]]) 01:13, 13 December 2021 (UTC)

==吴映红 Wú Yìnghóng 日语语言文学女 202120081530==

拉至宽处，驾上驯骡，出了西角门往东，过荣府正门，入一黑油漆大门内，至仪门前方下了车。邢夫人挽着黛玉的手进入院中。黛玉度其处必是荣府中之花园隔断过来的。
Pulled to a wide place, driving on the tame mule, out of the west corner gate to the east, past the main gate of Rongfu, into a black-painted gate, to the front of the ceremony door down the car. Mrs. Xing took Daiyu's hand and entered the courtyard. The first thing you need to do is to get to the garden.

Then he took the mule，went out the west Corner gate to the east, passed the main gate of Rongfu, entered a black painted gate, and got off in front of Yi gate. Lady Xing took Daiyu's hand and entered the courtyard. Daiyu spent its place must be the garden in the rong mansion partition come over.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 01:38, 15 December 2021 (UTC)

==肖毅瑶 Xiāo Yìyáo 英语语言文学（英美文学）女 202120081531==

进入三层仪门，果见正房、厢房、游廊悉皆小巧别致，不似那边的轩峻壮丽，且院中随处之树木山石皆好。及进入正室，早有许多艳妆丽服之姬妾、丫鬟迎着。邢夫人让黛玉坐了；一面令人到外书房中请贾赦。

When we entered the three-story ceremonial gate, the main room, wing room and verandah were all small and unique, unlike those of the other side. Besides, the trees, mountains and stones in the courtyard were all good. When they entered the main room, there were many concubines and servant girls dressed in colourful makeup and beautiful clothes waiting for them. Madam Xing asked Daiyu to sit down and then let others invite Jia She in the outer study.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 01:02, 15 December 2021 (UTC)

When entering the three- layers ceremonial gate, Daiyu found that the main room, wing room and verandah were all small and unique, unlike those of the other side. Besides, the trees, mountains and stones in the courtyard were all good. When they entered the main room, there were many concubines and servant girls dressed in heavy makeup and beautiful clothes waiting for them. Madam Xing asked Daiyu to sit down and then let others invite Jia She in the outer study.--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 12:10, 19 December 2021 (UTC)

==谢佳芬 Xiè Jiāfēn 英语语言文学（英美文学）女 202120081532==

一时回来说：“老爷说了：‘连日身上不好，见了姑娘，彼此伤心，暂且不忍相见。劝姑娘不必伤怀想家，跟着老太太和舅母，是和家里一样的。姐妹们虽拙，大家一处作伴，也可以解些烦闷。或有委屈之处，只管说，别外道了才是。’”

Mrs.Xing came back and said, "the master said, 'I've been felt not so good for days. I am afraid that I will be emotional if I see you, so I can't bear to see you for the time being. I advise you not to be homesick. It's the same as home to follow the old lady and aunt. Although the sisters are clumsy, you can relieve some boredom if you keep company together. If you have grievances, just tell us and make yourself at home.''--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 12:07, 19 December 2021 (UTC)

Mrs.Xing came back and said, "the master said, 'I've been felt not so good for days. I am afraid that I will be emotional if I see you, so I can't bear to see you for the time being. I advise you not to be homesick. It's the same as home to follow the old lady and aunt. Although the sisters are clumsy, you can relieve some boredom if you keep company together. If you have grievances, just tell us and make yourself at home.''--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:45, 20 December 2021 (UTC)

==谢庆琳 Xiè Qìnglín 俄语语言文学女 202120081533==

黛玉忙站起身来，一一答应了。再坐一刻便告辞，邢夫人苦留吃过饭去。黛玉笑回道：“舅母爱惜赐饭，原不应辞；只是还要过去拜见二舅舅，恐去迟了不恭，异日再领。望舅母容谅。”

Daiyu stood up and agreed one by one. Sitting for a moment and then said goodbye, Mrs. Xing painstakingly stay to eat a meal. Daiyu smile back: "aunt love to give rice, should not resign; just have to go over to see second uncle, afraid to go late disrespectful, another day to receive. I hope aunt forgive me."--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:44, 20 December 2021 (UTC)

==熊敏 Xióng Mǐn 英语语言文学（英美文学）女 202120081534==

邢夫人道：“这也罢了。”遂命两个嬷嬷用方才坐来的车送过去。于是黛玉告辞。邢夫人送至仪门前，又嘱咐了众人几句，眼看着车去了方回来。一时黛玉进入荣府，下了车，只见一条大甬路直接出大门来。

Mrs. Xing said: “That’s fine.” So she ordered two Sisters to send Daiyu back by Carriage used before. So Daiyu farewell others. Mrs. Xing saw her off and said some words to others, seeing the carriage come back and forth. Once Daiyu entered The House of Rong and got off the carriage, she saw a long and wide road.

Mrs. Xing said: “That’s fine.” So she ordered two Sisters to send Daiyu back by Carriage used before. So Daiyu farewell others. Mrs. Xing saw her off to the gate of etiquetteand said some words to others, seeing the carriage come back and forth. Once Daiyu entered The House of Rong and got off the carriage, she saw a long and wide road.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 11:26, 20 December 2021 (UTC)

==徐敏赟 Xú Mǐnyūn 语言智能与跨文化传播研究男 202120081535==

众嬷嬷引着，便往东转弯，走过一座东西穿堂，向南大厅之后，仪门内大院落：上面五间大正房，两边厢房，鹿顶耳房钻山，四通八达，轩昂壮丽，比各处不同。黛玉便知这方是正内室。

Led by the mammy, she turned east, passed through an east-west hall, and came to the south hall, where she found a large courtyard inside the Gate of Yi: five main rooms on the top, flanks on both sides, and deer's roof and ears, extending in all directions, magnificent and different from other places. Daiyu knew this was the inner room.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 09:10, 18 December 2021 (UTC)

Led by the mammies, they turned eastward and passed through an east-west hallway and the southward hall, she found a large courtyard inside the secondary gate: five main rooms on the top, flanks on both sides, and a small flat topped house next to the main house, extending in all directions, magnificent and different from other places. Daiyu knew this was the inner room.--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 10:08, 18 December 2021 (UTC)

==颜静 Yán Jìng 语言智能与跨文化传播研究女 202120081536==

进入堂屋，抬头迎面先见一个赤金九龙青地大匾，匾上写着斗大三个字，是“荣禧堂”；后有一行小字：“某年月日书赐荣国公贾源”，又有“万幾宸翰”之宝。大紫檀雕螭案上，设着三尺多高青绿古铜鼎，悬着待漏随朝墨龙大画，一边是錾金彝，一边是玻璃盆。

Entering the main room, I looked up and saw a great blue board framed in gilded dragons. On the plaque, there were two big words "Rongxi hall"; Then there is a line of small characters: "on a certain date, this was given to Jia Yuan, the Duke of Honor", and there was the treasure of Emperor's handwriting. On the large red sandalwood table that carved with dragon, there was a green bronze tripod more than three feet high, hanging a large ink dragon painting that seemed to attend the imperial court session in the early morning, with gilded wine vessels on one side and a glass basin on the other.--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 08:11, 18 December 2021 (UTC)

there was a green bronze tripod more than three feet high, hanging a large ink dragon painting that seemed to attend the imperial court session in the early morning, with gilded wine vessels on one side and a glass basin on the other.--[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 12:05, 19 December 2021 (UTC)

==颜莉莉 Yán Lìlì 国别女 202120081537==

地下两溜十六张楠木圈椅。又有一副对联，乃是乌木联牌镶着錾金字迹，道是：座上珠玑昭日月，堂前黼黻焕烟霞。下面一行小字是“世教弟勋袭东安郡王穆莳拜手书”。原来王夫人时常居坐宴息也不在这正室中，只在东边的三间耳房内。

On the ground two rows of 16 nanmu armchairs. There is also a pair of couplets, ebony couplet inset with gold handwriting, it said:The pearl and jade in the seat can shine with the sun and the moon; The people in front of the lobby wearing official clothes, its colors like clouds like clouds. The next line is written by Mu Shi, the hereditary king of Dongpyeong County, who is a brother who has been taught by your family for generations.For Lady King often sat and reposed not in this main room, but in the three eastern rooms.--[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 03:36, 12 December 2021 (UTC)

Since Lady King seldom sat in this main hall but used three rooms on the east side for relaxation.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 10:04, 14 December 2021 (UTC)

==颜子涵 Yán Zǐhán 国别女 202120081538==

于是嬷嬷们引黛玉进东房门来。临窗大炕上铺着猩红洋毯，正面设着大红金钱蟒引枕，秋香色金钱蟒大条褥；两边设一对梅花式洋漆小几：左边几上摆着文王鼎，鼎旁匙箸、香盒；右边几上摆着汝窑美人觚，里面插着时鲜花草。

So that the nannies led Mascara Jade Forest through the door of the eastern wing. The large kang by the window was covered with a scarlet foreign rug. In the middle were red back-rests and turquoise bolsters, both with dragon-design medallions, and a long greenish yellow mattress also with dragon medallions. On the two sides， stood one of a pair of small teapoys of foreign lacquer of plum-blossom pattern. On the left-hand table were a tripod, spoons, chopsticks and an incense container; On the right-hand table were a slender-waisted porcelain vase from the Ruzhou Kiln in which were placed seasonable flowers.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 09:48, 14 December 2021 (UTC)

Thereupon,the nurses led Daiyu through the door of the eastern wing. The large kang by the window was covered with a scarlet foreign rug. In the middle were red back-rests and turquoise bolsters, both with dragon-design medallions, and a long greenish yellow mattress also with dragon medallions. On the two sides stood on a pair of small teapoys of foreign lacquer of plum-blossom pattern. On the left-hand table were a tripod, spoons, chopsticks and an incense container; On the right-hand table were a slender-waisted porcelain vase from the Ruzhou Kiln in which were placed seasonable flowers.--[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 13:47, 14 December 2021 (UTC)

==阳佳颖 Yáng Jiāyǐng 国别女 202120081540==

地下面，西一溜四张大椅，都搭着银红撒花椅搭，底下四副脚踏；两边又有一对高几，几上茗碗、瓶花俱备。其馀陈设，不必细说。老嬷嬷让黛玉上炕坐。炕沿上却也有两个锦褥对设。

On the floor on the west side of the room, were four chairs in a row, all of which were covered with antimacassars, embroidered with silverish-red flowers.Beneath them stood four footstools. On either side, was also a pair of high teapoys which were covered with teacups and flower vases.The rest of the room need not be described in detail.
The nannies urged Mascara Jade Forest to sit on the kang, on the edge of which were two brocade cushions. --[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 13:42, 14 December 2021 (UTC)

On the floor facing on the west wall were four chairs in a row, all of which were covered with ornamented cloth embroidered with silverish-red flowers.Beneath them stood four footstools. On either side were a pair of high table with teacups and flower vases.Other decorations in the rest of the room need not be described in detail.The nannies urged Mascara Jade Forest to sit on the kang, on the edge of which were two brocade cushions.--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 09:50, 18 December 2021 (UTC)

==杨爱江 Yáng Àijiāng 英语语言文学（语言学）女 202120081541==

黛玉度其位次，便不上炕，只就东边椅上坐了。本房的丫鬟忙捧上茶来。黛玉一面吃了，打量这些丫鬟们妆饰衣裙，举止行动，果与别家不同。

Considering her status in the family, Daiyu sat on one of the chairs on the east side instead of sitting on the ''kang''. The maids in attendance served tea immediately. When she was sipping the tea, she observed the maids’ make-up,clothes and deportment, which, her thought, were indeed quite different from those in other families.--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 09:38, 18 December 2021 (UTC)

Considering her status in the family, Mascara Jade sat on one of the chairs on the east side instead of sitting on the ''kang''. The maids in attendance served tea immediately.Sipping the tea, she observed the maids’ make-up,clothes and deportment, which, her thought, were indeed quite different from those in other families.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 14:18, 18 December 2021 (UTC)

==杨堃 Yáng Kūn 法语语言文学女 202120081542==

茶未吃了，只见一个穿红绫袄、青绸掐牙背心的一个丫鬟走来笑道：“太太说，请林姑娘到那边坐罢。”老嬷嬷听了，于是又引黛玉出来，到了东廊三间小正房内。

Before the tea was drunk, a servant girl wearing a red silk jacket and a green satin vest came up and smiled, "Mrs. Wang invited Miss Lin to come and sit over there." When the old Mammy heard this, she led Daiyu out again and went to the third small main room on the east porch.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 03:33, 12 December 2021 (UTC)

Before they drank tea over, a servant girl in a red silk jacket and a green satin vest came up and smiled, "Mrs. Wang invited Miss Lin to come and sit over there." When the old Mammy heard this, she led Daiyu out again to the third small main room on the east porch.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 11:10, 12 December 2021 (UTC)

==杨柳青 Yáng Liǔqīng 英语语言文学（英美文学）女 202120081543==

正面炕上横设一张炕桌，上面堆着书籍、茶具；靠东壁面西设着半旧的青缎靠背、引枕。王夫人却坐在西边下首，亦是半旧青缎靠背、坐褥。见黛玉来了，便往东让。

On the kang there was a kang table on which books and tea sets piled up. Half new backrests and pillows made of blue satins were set on the east side of the wall. However, Mrs. Wang set at the foot of the west wall where half new backrests and mattresses made of blue satins were displayed. Mrs. Wang moved to the east side when she saw Lin Daiyu come in.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 11:11, 12 December 2021 (UTC)

On the kang lies a kang table,on which books and tea sets are piled up. Half new backrests and pillows made of blue satins were put on the east side of the wall. However, Mrs. Wang sat at the foot of the west wall where half new backrests and mattresses made of blue satins are displayed. Mrs. Wang moved to the east side when she saw Daiyu coming in.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 12:11, 19 December 2021 (UTC)

==叶维杰 Yè Wéijié 国别男 202120081544==

黛玉心中料定这是贾政之位。因见挨炕一溜三张椅子上也搭着半旧的弹花椅袱，黛玉便向椅上坐了。王夫人再三让他上炕，他方挨王夫人坐下。王夫人因说：“你舅舅今日斋戒去了，再见罢。

Daiyu thought it must be Jia Zhen's seat. Seeing that there were half-old bouncing chair blankets on the three chairs slid by the kang, Daiyu sat on the chair. Mrs. Wang repeatedly asked him to go to the kang, then she sat down next to Mrs. Wang. Mrs. Wang said: "Your uncle has gone fast today, goodbye.

Mascara Jade thought that this was Master Merchant's seat， because she saw that there were three chairs next to the bed with a half-used chair, so Mascara Jade sat down on the chair. She sat down next to Lady King after she had asked her to go to the bed again and again. Lady King said, "Your uncle went to fast today, see you later.”--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 12:29, 19 December 2021 (UTC)Yi Yangfan

==易扬帆 Yì Yángfān 英语语言文学（英美文学）女 202120081545==

只是有句话嘱咐你：你三个姐妹倒都极好，以后一处念书认字，学针线，或偶一玩笑，却都有个尽让的。我就只一件不放心：我有一个孽根祸胎，是家里的混世魔王，今日因往庙里还愿去，尚未回来，晚上你看见就知道了。

I just have one thing to tell you: your three sisters are all very good, and in the future they will study and learn to read and write together, and learn to sew, or occasionally play jokes, but all of them will do their best. There is only one thing I am not sure about: I have a sinful child who is the evil one in my family, and he has not returned yet because he has gone to the temple to pay his respects.--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 02:19, 13 December 2021 (UTC)Yi Yangfan

I just want to remind you: your sisters are very kind , and in the future you will study together, and learn to read and write and learn to sew. Sometimes you will play jokes at each other, but you will be very tolerant to each other. There is only one thing I am worried about: there is a naughty boy in our family, and he has not returned yet because he has gone to the temple to redeem his wishes, you will see him in the evening.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 07:45, 13 December 2021 (UTC)

==殷慧珍 Yīn Huìzhēn 英语语言文学（英美文学）女 202120081546==

你以后总不用理会他，你这些姐姐妹妹都不敢沾惹他的。”黛玉素闻母亲说过：“有个内侄，乃衔玉而生，顽劣异常，不喜读书，最喜在内帏厮混。外祖母又溺爱，无人敢管。”

“You can ignore him later and none of your sisters dare to bother him. ” Daiyu heard from her mother: “I have a nephew, who was born with jade in his mouth. He is very naughty and don’t like to read, but prefer to play with girls. His grandma has always spoiled him so that everyone let him be. ”--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 07:27, 13 December 2021 (UTC)

"You can ignore him in future because none of your sisters dare to mess up with him". Mascara Jade has long heard from her mother about him: "I have a nephew, born with a jade in his mouth, who is very naughty and doesn’t like to read, but prefers to hang around with girls. His grandma has always spoiled him so that everyone let him be". --[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 12:31, 19 December 2021 (UTC)

==殷美达 Yīn Měidá 英语语言文学（语言学）女 202120081547==

今见王夫人所说，便知是这位表兄。一面陪笑道：“舅母所说，可是衔玉而生的？在家时，记得母亲常说：这位哥哥比我大一岁，小名就叫宝玉，性虽憨顽，说待姊妹们却是极好的。

What Lady King described today is the cousin for sure. Mascara Jade said while smiling:" Is the person you just mentioned my cousin born with a jade? I remember when I was at home my mother often said that the cousin nicknamed Precious Jade is one year older than me. Although he is a little mischievous, he is very friendly with his sisters".--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:27, 12 December 2021 (UTC)

Who Lady King described today is the cousin for sure. Mascara Jade said while smiling:" Is this my cousin you just mentioned born with a jade? I remember when I was at home my mother often said that the cousin nicknamed Precious Jade is one year older than me. Although he is a little mischievous, he is very friendly with his sisters".--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 12:06, 19 December 2021 (UTC)

==尹媛 Yǐn Yuán 英语语言文学（英美文学）女 202120081548==

况我来了，自然和姊妹们一处，弟兄们是另院别房，岂有沾惹之理？”王夫人笑道：“你不知道原故。他和别人不同，自幼因老太太疼爱，原系和姐妹们一处娇养惯了的。

Now I come here,undoubtfully I live with my sisters. The brothers are in some different houses. Is there any reason to mess with them?" Lady King smiled and said, "You don't know. Unlike the others, he had been coddled by his sisters since he was young for the love of Grandma Merchant.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 15:30, 13 December 2021 (UTC)

Now I come here,undoubtfully I live with my sisters. The brothers are in some different houses. Is there any reason to mess with them?" Lady King smiled and said, "You don't know the reason. Unlike others, he had been coddled by his sisters since he was young for the love of Grandma Merchant.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 03:20, 15 December 2021 (UTC)

==詹若萱 Zhān Ruòxuān 英语语言文学（英美文学）女 202120081549==

若姐妹们不理他，他倒还安静些；若一日姐妹们和他多说了一句话，他心上一喜，便生出许多事来：所以嘱咐你别理会他。他嘴里一时甜言蜜语，一时有天没日，疯疯傻傻，只休信他。”黛玉一一的都答应着。

“If the sisters ignore him, he is a bit quieter: if one day the sisters talk to him more, he is so happy that he will stir up many troubles: so I tell you to ignore him. He may talk sweetly for a while, and he may be crazy and silly for a while, just don't believe him.” Daiyu replied one by one.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 08:45, 13 December 2021 (UTC)
If the sisters ignore him, he will be quiet; if one day they talk to him more, he will be happy, and many things will happen: so I tell you to ignore him. His mouth a sweet talk, a moment there is no day, crazy and silly, just do not believe him. Daiyu agreed one by one.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 12:06, 19 December 2021 (UTC)

==张秋怡 Zhāng Qiūyí 亚非语言文学女 202120081550==

忽见一个丫鬟来说：“老太太那里传晚饭了。”王夫人忙携了黛玉，出后房门，由后廊往西，出了角门，是一条南北甬路，南边是倒座三间小小抱厦厅，北边立着一个粉油大影壁，后有一个半大门，小小一所房屋。
Suddenly see a servant girl to say: "old lady there spread supper." Lady King and Mascara Jade Forest went out of the back door, leading from the back corridor to the west and out of the corner gate. There was a north-south corridor, with three small rooms in the south, a big screen wall of powder and oil in the north, and a small house with a half gate behind.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 13:53, 12 December 2021 (UTC)

Suddenly a servant girl said, "the old lady has passed on dinner." Lady King hurriedly took Mascara Jade Pearl out of the back door, from the back porch to the west, out of the corner door. It is a North-South corridor. In the south is the inverted three small balcony halls. In the north is a oil-powdered large shadow wall, followed by a half gate and a small house.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 12:28, 13 December 2021 (UTC)

==张扬 Zhāng Yáng 国别男 202120081551==

王夫人笑指向黛玉道：“这是你凤姐姐的屋子。回来你好往这里找他去，少什么东西，只管和他说就是了。”这院门上也有几个才总角的小厮，都垂手侍立。王夫人遂携黛玉穿过一个东西穿堂，便是贾母的后院了。

Lady King smiled at Mascara Jade Pearl and said: "This is your sister Phoenix's house. If you come back, you can find her here. And if there's anything missing, just tell her." On the gate of the courtyard, there were also several young boys who were only in their childhood, all standing with their hands down. Lady King then took Mascara Jade Pearl through an east-west hall, which was Grandma Merchant's backyard.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 07:30, 11 December 2021 (UTC)

Lady King smiled at Mascara Jade Pearl and said: "This is your sister Phoenix's house. If you come back, you can find her here. And if there's anything missing, just tell her." On the gate of the courtyard,there were also a few young boys on the door of this courtyard, all standing with their hands down.. Lady King then took Mascara Jade Pearl through an east-west hall, which was Grandma Merchant's backyard.

==张怡然 Zhāng Yírán 俄语语言文学女 202120081552==

于是进入后房门，已有许多人在此伺候，见王夫人来，方安设桌椅；贾珠之妻李氏捧杯，熙凤安箸，王夫人进羹。贾母正面榻上独坐，两旁四张空椅。熙凤忙拉黛玉在左边第一张椅子上坐下，黛玉十分推让。

So they entered the back room, where many people were already waiting, and when they saw Lady King coming, they placed the table and chairs; Li, wife of Treasure Merchant, held the cup, Lady King placed the chopsticks, and Splendid Phoenix King drank the soup. Grandma Merchant was sitting alone on a couch, flanked by four empty chairs. Splendid Phoenix King was busy pulling Mascara Jade Forest to sit in the first chair on the left, but Mascara Jade Forest was too embarrassed to sit.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 00:57, 13 December 2021 (UTC)

So they entered the back room, where many people were already waiting, and when they saw Lady King coming, they placed the table and chairs; Li, wife of Treasure Merchant, held the cup, Lady King placed the chopsticks, and Splendid Phoenix King drank the soup. Grandma Merchant was sitting alone on a couch, flanked by four empty chairs. Splendid Phoenix King was busy pulling Mascara Jade Forest to sit in the first chair on the left, but Mascara Jade Forest was too embarrassed to sit.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 03:42, 13 December 2021 (UTC)

==钟义菲 Zhōng Yìfēi 英语语言文学（英美文学）女 202120081553==

贾母笑道：“你舅母和嫂子们是不在这里吃饭的。你是客，原该这么坐。”黛玉方告了坐，就坐了。贾母命王夫人也坐了。迎春姊妹三个告了坐，方上来：迎春坐右手第一，探春左第二，惜春右第二。

Grandama Merchant said with a smile, "your aunt and sister-in-law don't eat here. You are a guest. You should have sat here." Mascara Jade Forest then sat down. Grandama Merchant ordered Lady King to sit down. The three sisters of Spring Pleasure Merchant sat down：Spring Pleasure Merchant sat first on the right hand, Seeking-Spring Merchant second on the left, and Cherishing Spring Merchant second on the right.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 10:36, 11 December 2021 (UTC)

Grandama Merchant said with a smile, "your aunts and sisters-in-law don't eat here. You are a guest. You should have sat here." Mascara Jade Forest then sat down. Grandama Merchant ordered Lady King to sit down. The three sisters of Spring Pleasure Merchant were asked to sit down: Spring Pleasure Merchant sat first on the right hand, Seeking-Spring Merchant second on the left, and Cherishing Spring Merchant second on the right.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 02:02, 12 December 2021 (UTC)

==钟雨露 Zhōng Yǔlù 英语语言文学（英美文学）女 202120081554==

旁边丫鬟执着拂尘、漱盂、巾帕，李纨、凤姐立于案边布让；外间伺候的媳妇、丫鬟虽多，却连一声咳嗽不闻。饭毕，各各有丫鬟用小茶盘捧上茶来。当日林家教女以惜福养身，每饭后必过片时方吃茶，不伤脾胃；

Standing at the table, the servant girls held the horsetail whisks, vessels for mouthwash and handkerchiefs. Silk Plum and Splendid Phoenix King sent dishes, refreshments to guests and invited them to eat. Though there were many servant girls in the outer room, they could not be heard to utter a sound. When the meal was over, each servant girl brought tea with a small tray. Mascara Jade Forest took tea after each meal to keep health and not hurt her spleen and stomach.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 01:55, 12 December 2021 (UTC)

The servant girls are standing at the table with the horsetail whisks, vessels for mouthwash and handkerchiefs. Silk Plum and Splendid Phoenix King sent dishes, refreshments to guests and invited them to eat. Though there were many servant girls in the outer room, they could not be heard to utter a sound. When the meal was over, each servant girl brought tea with a small tray. Mascara Jade Forest took tea after each meal to keep health and not hurt her spleen and stomach.--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 09:23, 13 December 2021 (UTC)

[[Media:Example.ogg]]==周玖 Zhōu Jiǔ 英语语言文学（英美文学）女 202120081555==

今黛玉见了这里许多规矩不似家中，也只得随和些。接了茶，又有人捧过漱盂来，黛玉也漱了口，又盥手毕。然后又捧上茶来，这方是吃的茶。贾母便说：“你们去罢，让我们自在说说话儿。”
Mascara Jade Forest saw many rules here are not like her home. She was also easy-going. After receiving the tea, someone else took a gargle bowl for her. Mascara Jade Forest also rinsed her mouth and finished washing her hands again. Then tea which was for drinking was brought in. Then Grandma Merchant said to servants , "You all go and let's have a talk in our own comfort."

Now Mascara Jade saw many rules here are not like the rules of her home. She can only be easygoing. She caught the teacup. Some domestics came over with a mouthwash basin. Mascara Jade gargled and washed her hands. Then the servant brought back tea, and this was tea for drinking.Then Dowager Lady Jia said to servant, "You all go and let's have a talk in our own comfort."--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 10:47, 13 December 2021 (UTC)

==周俊辉 Zhōu Jùnhuī 法语语言文学女 202120081556==

王夫人遂起身，又说了两句闲话儿，方引李、凤二人去了。贾母因问黛玉念何书，黛玉道：“刚念了《四书》。”黛玉又问姊妹读何书，贾母道：“读什么书，不过认几个字罢了。”

Lady King stood up and said something idle, then led Lady Plum and Splendid Phoenix King to leave. When Dowager Lady Jia asked Mascara Jade what books she had read, Mascara Jade replied, "I just have read the ''Four Books''." When Mascara Jade asked her sisters what books they read, Dowager Lady Jia said, "They don't read anything. They only know a few words."--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 09:25, 13 December 2021 (UTC)

Lady King rose as soon as she heard these words, and having made a few irrelevant remarks, she led the way and left the room along with the two ladies, Mrs. Li and Splendid Phoenix king.Grandma Merchant, having inquired of Mascara Jade what books she was reading, "I have just begun reading the Four Books," Mascara Jade replied. "What books are my cousins reading?" Mascara Jade went on to ask. "Books, you say!" exclaimed Grandma Merchant; "why all they know are a few characters, that's all."--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:15, 15 December 2021 (UTC)

==周巧 Zhōu Qiǎo 英语语言文学（语言学）女 202120081557==

一语未了，只听外面一阵脚步响，丫鬟进来报道：“宝玉来了。”黛玉心想：“这个宝玉，不知是怎样个惫懒人呢。”及至进来一看，却是位青年公子：头上戴着束发嵌宝紫金冠，齐眉勒着二龙戏珠金抹额；

The sentence was barely out of her lips, when a continuous sounding of footsteps
was heard outside, and a waiting maid entered and announced that Precious Jade was
coming. Mascara Jade was speculating in her mind how it was that this Precious Jade had
turned out such a good-for-nothing fellow, when he happened to walk in.
He was, in fact, a young man of tender years, wearing on his head, to hold his
hair together, a cap of gold of purplish tinge, inlaid with precious gems.
Parallel with his eyebrows was attached a circlet, embroidered with gold, and
representing two dragons snatching a pearl.
--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 08:36, 13 December 2021 (UTC)

After a word, only a sound of footsteps outside, the maid came in and reported: "Baoyu is here." Daiyu thought to herself: "This Baoyu, I don't know what a tired lazy person." When she came in, she was a young man. He wears a purple and gold crown with hair inlaid on his head, and his forehead are tied with gold frontlet（The shape is two dragons playing with pearled）.--[[User:Zhou Qing|Zhou Qing]] ([[User talk:Zhou Qing|talk]]) 15:21, 11 December 2021 (UTC)

==周清 Zhōu Qīng 法语语言文学女 202120081558==

一件二色金百蝶穿花大红箭袖，束着五彩丝攒花结长穗宫绦，外罩石青起花八团倭缎排穗褂；登着青缎粉底小朝靴。面若中秋之月，色如春晓之花；鬓若刀裁，眉如墨画，鼻如悬胆，睛若秋波。

A big red arrow sleeve decorated with two-color golden butterfly flowers, is tied with multicolored silk and knotted with long spikes, and is covered with azurite and satin rowed gowns; it wears small green satin and powder-soled boots. The face is as round and beautiful as the moon of Mid-Autumn Festival, the complexion is like a flower of spring dawn; the temples are like a knife cut, the eyebrows are like ink painting, the nose is like a hanging gall, and the eyes are like autumn waves.

A big red arrow sleeve decorated with two-color golden butterfly flowers, is tied with multicolored silk and knotted with long spikes, and is covered with azurite and satin rowed gowns; he wore small green satin and powder-soled boots. The face is as round and beautiful as the moon at mid-autumn, the complexion is like a flower of in spring; the temples as if chiselled with a knife, the eyebrows are like ink painting, the nose is like a a well-cut and shapely nose, and the eyes are like vernal waves.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 06:19, 13 December 2021 (UTC)

==周小雪 Zhōu Xiǎoxuě 日语语言文学女 202120081559==

虽怒时而似笑，即嗔视而有情。项上金螭缨络，又有一根五色丝绦，系着一块美玉。黛玉一见，便吃一大惊，心中想道：“好生奇怪：倒像在那里见过的，何等眼熟！”只见这宝玉向贾母请了安，贾母便命：“去见你娘来。”

His angry look even resembled a smile; his glance was full of sentiment.Round his neck he had a gold dragon necklet with a fringe; also a cord of variegated silk, to which was attached a piece of beautiful jade. When Mascara Jade Forest saw this, she was shocked."How very strange." she was reflecting in her mind; "it would seem as if I had seen him somewhere or other, for his face appears extremely familiar to my eyes;" Precious Jade Merchant greeted Grandma Merchant "Go and see your mother and then come back," remarked her venerable ladyship.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 06:08, 13 December 2021 (UTC)

His angry look somentimes even resembled a smile; his glance was full of sentiment.Round his neck he had a gold dragon necklet with a fringe; also a cord of silk of five colours, to which was attached a piece of beautiful jade. When Mascara Jade Forest saw this, she was shocked and thought to herself: "How strange it is." she was reflecting in her mind; "as if I had seen him somewhere or other, for his face appears extremely familiar to my eyes;" Precious Jade Merchant greeted Lady Dowager "Go and see your mother and then come back."--[[User:Zhu Suzhen|Zhu Suzhen]] ([[User talk:Zhu Suzhen|talk]]) 11:46, 16 December 2021 (UTC)

==朱素珍 Zhū Sùzhēn 英语语言文学（语言学）女 202120081561==

即转身去了。一会再来时已换了冠带：头上周围一转的短发都结成小辫，红丝结束，共攒至顶中胎发，总编一根大辫，黑亮如漆，从顶至梢，一串四颗大珠，用金八宝坠脚；身上穿着银红撒花半旧大袄；仍旧带着项圈、宝玉、寄名锁、护身符等物；

Then turned around and went. He has changed the crown band when coming back for a while: the short hair around the head is braided, the red silk ends, and the hair is gathered up to the top of the fetus. The chief editor is a big braid, black and shiny, from top to tip , A string of four large beads, with gold eight treasures falling to the feet; wearing a silver-red half-old coat with flowers; still wearing collars, gems, locks, amulets, etc.;

He turned away. When he came back later, he had changed his crown belt: the short hair around his head was braided, and the red silk ended. He saved up to the top and middle fetal hair. The chief editor had a big braid, black and bright as paint, a string of four big beads from the top to the tip, and dropped his feet with gold eight treasures; He was wearing a silver red flower sprinkled semi-old coat; Still wearing collars, precious jade, name sending locks, amulets, etc--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 12:56, 16 December 2021 (UTC)

==邹岳丽 Zōu Yuèlí 日语语言文学女 202120081562==

下面半露松绿撒花绫裤，锦边弹墨袜，厚底大红鞋。越显得面如傅粉，唇若施脂；转盼多情，语言若笑。天然一段风韵，全在眉梢；平生万种情思，悉堆眼角。看其外貌，最是极好，却难知其底细。
His lower body showed loose green flower pants, cotton socks and a pair of thick soled red shoes. This makes him look more beautiful. The lips seem to have been powdered with rouge; When he speaks, he often has a smile on his face, and his eyebrows can convey affection. A person's style and temperament, including what he thinks, can be conveyed through his eyes. His appearance is very good-looking, but I don't know whether he has real connotation.

==Nadia 202011080004==

后人有《西江月》二词批的极确，词曰：

==Mahzad Heydarian 玛莎 202021080004==

无故寻愁觅恨，有时似傻如狂。
Seeking sorrow and hate for no reason, sometimes seems stupid and crazy.

==Mariam toure 2020GBJ002301==

纵然生得好皮囊，腹内原来草莽。

==Rouabah Soumaya 202121080001==

潦倒不通庶务，愚顽怕读文章。

I'm not able to get through general affairs, and I'm afraid of reading articles.

==Muhammad Numan 202121080002==

行为偏僻性乖张，那管世人诽谤。
He who behaves in a perverse way has no control over the slander of course.--[[User:Atta Ur Rahman|Atta Ur Rahman]] ([[User talk:Atta Ur Rahman|talk]]) 03:29, 14 December 2021 (UTC)

==Atta Ur Rahman 202121080003==

又曰：富贵不知乐业，贫穷难耐凄凉。
It is also known that wealth does not know pleasure and happiness, and poverty cannot endure loneliness.

==Muhammad Saqib Mehran 202121080004==

可怜辜负好时光，于国于家无望。
Translation: The poor lived up to the good times, and the country was hopeless at home.

==Zohaib Chand 202121080005==

天下无能第一，古今不肖无双。

==Jawad Ahmad 202121080006==

寄言纨袴与膏粱，莫效此儿形状。

English; the author is to give some suggestion to playboys of high official that they do not follow the example of Jia Baoyu.

==Nizam Uddin 202121080007==

却说贾母见他进来，笑道：“外客没见就脱了衣裳了，还不去见你妹妹呢。”

But she said that Mother Jia saw him come in and smiled: "The foreigner took off her clothes without seeing him, so she won't go to see your sister."

==Öncü 202121080008==

宝玉早已看见了一个袅袅婷婷的女儿，便料定是林姑妈之女，忙来见礼。

Precious Jade had already seen a daughter with a gentle posture, thought might be the daughter of Aunt Lin, then hurried to meet her.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 04:17, 13 December 2021 (UTC)

==Akira Jantarat 202121080009==

归了坐细看时，真是与众各别。

When I look at you carefully, I think you are different.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 09:59, 13 December 2021 (UTC)

When I returned to take a closer look, it was really different. --[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 07:41, 12 December 2021 (UTC)

==Benjamin Wellsand 202111080118==

只见：两弯似蹙非蹙笼烟眉，一双似喜非喜含情目。

I saw two bends like the frowning of smoked eyebrows, at first they seemed happy but not really happy, yet affectionate eyebrows. --[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 07:41, 12 December 2021 (UTC)

I saw: two curved eyebrows that looked like a frown, a pair of eyebrows that seemed to be happy or not. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 23:18, 12 December 2021 (UTC)

==Asep Budiman 202111080020==

态生两靥之愁，娇袭一身之病。

The sorrow of the two distresses, the disease of the whole body. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 23:17, 12 December 2021 (UTC)

The sorrow of two distresses, spoiled - the disease of the whole body.------Ei Mon Kyaw [[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:15, 15 December 2021 (UTC)--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:15, 15 December 2021 (UTC)Ei Mon Kyaw

==Ei Mon Kyaw 202111080021==

泪光点点，娇喘微微。

Tears shone a little, and she breathed slightly.--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:47, 15 December 2021 (UTC)Ei Mon Kyaw -----Ei Mon Kyaw[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 09:47, 15 December 2021 (UTC)
The tears droped, and she breathed slowly. --[[User:Mahzad Heydarian|Mahzad Heydarian]] ([[User talk:Mahzad Heydarian|talk]]) 11:58, 15 December 2021 (UTC)

The eyes twinkled with tears and she breathed slightly.--[[User:Chen Jing|Chen Jing]] ([[User talk:Chen Jing|talk]]) 12:18, 19 December 2021 (UTC)

20211124 homework

2021-12-29T08:54:17Z

Wei Yiwen: /* 王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525 */

Quicklinks: [[Introduction_to_Translation_Studies_2021|Back to course homepage]] [https://bou.de/u/wiki/uvu:Community_Portal#Frequently_asked_questions_FAQ FAQ] [https://bou.de/u/wiki/uvu:Community_Portal Manual] [[20210926_homework|Back to all homework webpages overview]] [[20220112_final_exam|final exam page]]

==陈静 Chén Jìng 国别女 202020080595==

我很纳闷：《不自弃文》是篇名，《姬子》是书名，应该同等对待，要么都予注释，要么都不注释，为什么一注一不注呢？难道前者生僻而需要注释，后者人所共知而不必注释吗？显然不是，只能说是避难就易，这与注释的宗旨完全背道而驰。
I wonder that since No Self-surrender is the title of the passage and Jizi is the title of the book, which should be treated equally, why did the situation happened that one annotated while one did not? Did the former need to be annotated while the latter is known to all without having to be annotated? Obviously, it is for choosing the easier way, which is completely contrary to the purpose of the annotation.

I wonder: "don't abandon yourself" is the title, and "Ji Zi" is the title of the book. It should be treated equally, either annotated or not annotated. Why not annotate one note at a time? Is it true that the former is remote and needs annotation, while the latter is well known and does not need annotation? Obviously not, it can only be said that it is easy to avoid difficulties, which is completely contrary to the purpose of the notes.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 07:01, 24 November 2021 (UTC)

==蔡珠凤 Cài Zhūfèng 法语语言文学女 202120081477==

那怕注为“《姬子》不详”，也还不失为态度诚实。老实说，起初我对《姬子》也一头雾水，因为见所未见，闻所未闻。但根据我自定的注释原则，我不能回避。

Even if it is noted as "Ji Zi" unknown ", it can be regarded as an honest attitude. To be honest, at first I was confused about Ji Zi, because I had never seen or heard of it. But according to my own annotation principle, I can't avoid it.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 11:20, 21 November 2021 (UTC)

Even if it is noted as "unknown Ji Zi" , it can still be regarded as an honest attitude. To be honest, at first I was confused about ''Ji Zi'', because I had never seen or heard of it. But according to my own annotation principle, I can't avoid it.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 14:36, 22 November 2021 (UTC)Chen Huini

==陈惠妮 Chén Huìnī 英语语言文学（英美文学）女 202120081479==

于是我首先求助于《中国古典数字工程》，肯定了中国根本不存在《姬子》这么一本书，完全是曹雪芹所杜撰，正如《古今人物通考》、《中国历代文选》都是曹雪芹杜撰一样。其次，我记得俞平伯先生有一篇专门解释《姬子》的文章，但文章的题目、发表时间以及文章内容却不记得了。经过两天的翻箱倒柜，我终于找到了这篇文章，它的题目是《读〈红楼梦〉随笔》第九节《姬子》，初载于《文汇报》1954年1月25日；又收入《红楼梦研究参考资料选辑》第二辑，人民文学出版社1973年11月出版。

Therefore, I first made reference htiw "Chinese Classical Digital Engineering" and confirmed that there was no such a book called "Ji Zi" in China, which was completely written by Cao Xueqin, just as Cao Xueqin wrote "General Examination of Ancient and Modern Characters" and "Selected Chinese Writings in Past Dynasties". Secondly, I remember that Mr. Yu Pingbo had a special article explaining ''JiZi'', but I do not remember the title, publication time and content of the article. After two days of searching, I finally found this article. Its title is ''Ji Zi'', section 9 of Essays on Reading ''A Dream of Red Mansion''. It was first published in Wenhui Daily on January 25, 1954. It was also included in the second series of ''Selected Research Reference Materials on A Dream of Red Mansion'', published by People's Literature Publishing House in November 1973.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 14:46, 22 November 2021 (UTC)Chen Huini

So, I firstly searched ''Chinese Classical Digital Engineering'' and confirmed there was no such a book called "Ji Zi" in China. This book was completely made up by Cao Xueqin like the same thing he did to ''General Examination of Ancient and Modern Characters'' and ''Selected Chinese Writings in Past Dynasties''.Then, I recalled that Mr. Yu Pingbo especially wrote an article to explain ''Ji Zi'', but I didn't remember the title, publication time and content.After two days of searching, I finally found it. The title of it was ''Ji Zi'', section 9 of Essays on Reading ''A Dream of Red Mansion'' which was first published in Wenhui Daily on January 25, 1954. and then was included in the second series of ''Selected Research Reference Materials on A Dream of Red Mansion'', published by People's Literature Publishing House in November 1973.--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:20, 24 November 2021 (UTC)

==陈湘琼 Chén Xiāngqióng 外国语言学及应用语言学女 202120081480==

据俞先生在文章中说：姬子书到底是部什么书呢，谁也说不上来。特别前些日子把这一回书选为高中国文的教材，教员讲解时碰到问题，每来信相询，我亦不能对。但经过研究，他还是写了这篇文章，作为回答。

According to Mr.Yu in his article: nobody can tell what book ''Ji Zi'' really is. Moreover, this chapter of ''A Dream in Red Mansions'' with the name ''Ji Zhi'' has been selected as the reading material of the high school,and I can't say anything when the teacher who failed to explain it in the classroom come to me.But after careful research, he still write an article to reply this question.

According to Mr. Yu in his article: nobody can tell what book ''Ji Zi'' really is. In particular, this chapter was selected as a reading material for the Chinese language in high school some days ago, the teachers encountered problems when explaining it, and they wrote to me every time to ask about it, but I couldn't get it right. But after researching, he wrote this article as an answer.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:37, 23 November 2021 (UTC)

==陈心怡 Chén Xīnyí 翻译学女 202120081481==

他的结论有三点：其一，《姬子》是“作者杜撰”，并以第三回的《古今人物通考》也是杜撰而作为佐证。其二，“这原来是一个笑话”，是探春“拿姬子来抵制”宝钗用以压人的朱子和孔子，而“比朱子孔子再大，只好是姬子了。殆以周公姓姬，作为顽笑”。

There are three points in his conclusion: one, ''Ji Zi'' is "the author fabricated", and to the third round of " the general examination of ancient and modern characters" is also fabricated and as proof. Second, "this turns out to be a joke", is Tanchun " take ''Ji Zi'' to resist" Baochai and used to press people by citing Zhu Zi and Confucius, and "higher level than Zhu Zi and Confucius can only be ''Ji Zi''. Probably Zhou Gong was surnamed Ji as a joke.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:35, 23 November 2021 (UTC)
There are three points in his conclusion: first, ''Ji Zi'' is "fabricated by the author", and can be proved by the fabrication of the third round of " the general examination of ancient and modern characters". Second, "this turns out to be a joke", which Tanchun " held ''Ji Zi'' to resist” Baochai who used to press her by citing Zhu Zi and Confucius, but “requiring higher level than Zhu Zi and Confucius, there’s only be ''Ji Zi''. Probably Zhou Gong was surnamed Ji as a joke.”--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 12:25, 23 November 2021 (UTC)

==程杨 Chéng Yáng 英语语言文学（英美文学）女 202120081482==

其三，“有人或者要问为什么净瞎捣乱，造书名？我回答：这是小说。”《中国古典数字工程》可以证明俞先生的“杜撰说”是正确的，因此我把俞先生的意见用以注释《姬子》。
Thirdly, "Someone may ask why messing around and making a title? I replied: This is a novel. "It can be proved by ''The Chinese Classical Digital Engineering'' that Mr. Yu’s “theory of fabrication” is correct. Therefore, I applied Mr. Gong's opinion to annotate ''Jizi''.--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 04:56, 23 November 2021 (UTC)

Thirdly, "Someone may ask why to mess around and make a title? I replied: This is a novel. "It can be proved by ''The Chinese Classical Digital Engineering'' that Mr. Yu’s ''Theory of Fabrication'' is correct. Therefore, I applied Mr. Gong's opinion to annotate ''Ji Tzu''.--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 11:01, 26 November 2021 (UTC)

==丁旋 Dīng Xuán 英语语言文学（英美文学）女 202120081483==

据我所知，现在有人搜集了周公的几篇佚文，将其编为集子，按照《老子》、《庄子》、《孟子》之类的惯例，即命名为《姬子》，但这与曹雪芹毫不相干，《红楼梦》中的《姬子》书名绝对是杜撰。此外，有的注本虽然对《不自弃文》作了注释，却只是简述该文的大意，而没有注出曹雪芹的深刻用意。原来朱熹的徒子徒孙认为此文格调低下，有失朱夫子的身份，故将此文排除在众多朱熹文集之外，只有明·朱培编《文公大全集补遗》卷八从抄本《朱熹家谱》中引录，另有《朱子文集大全类编·卷二一·庭训》亦予收录。

As far as I know, someone collected several lost articles of Duke of Zhou, edited them into an anthology and named it ''Ji Tzu'' according to the routine of ''Lao Tzu'', ''Chang Tzu'' and ''Mencius'' and so on. However, this thing is irrelevant to Cao Xueqin, so the title of ''Ji Tzu'' in ''A Dream in Red Mansions'' is absolutely fabricated. Besides, although some books with annotations made interpretation to ''No Self-surrender'', they just told the main idea of this article rather than annotating the deep meaning made by Cao Xueqin. In fact, disciples and followers of Zhu Xi thought the style of this passage beneath his dignity is very low, so they excluded it out of many anthologies of Zhu Xi. Only when Zhu Pei(Ming dynasty) edited the eighth roll of ''Supplement to Collected Works of Duke Wen'', he incited it from transcript of ''Zhu Xi’s Genealogy''. In addition, it is also included in ''Complete Works of Zhu Tzua•Roll Twenty-one•Home Hearing''.--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 03:47, 21 November 2021 (UTC)

As far as I know, now someone collected several lost articles of Duke of Zhou and edited them into a collection that was named ''Ji Tzu'' according to the routine of ''Lao Tzu'', ''Chang Tzu'' and ''Mencius'' and so on. However, this thing is irrelevant to Cao Xueqin, so the title of ''Ji Tzu'' in ''A Dream in Red Mansions'' is absolutely fabricated. Besides, although some books with annotations made interpretations to ''No Self-surrender'', they just briefly described the main idea of this article rather than annotating the deep meaning of Cao Xueqin. In fact, disciples and followers of Zhu Xi thought this passage was low in style and demeaned Zhu Xi, so they excluded it out of many anthologies of Zhu Xi. Only when Zhu Pei(Ming dynasty) edited the Book Eight of ''Supplement to Collected Works of Duke Wen'', he incited it from transcript of Zhu Xi’s Genealogy. In addition, ''Complete Works of Zhu Tzua• Book Twenty-one•Home Hearing'' was also included.--[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 03:07, 22 November 2021 (UTC)

==杜莉娜 Dù Lìna 英语语言文学（语言学）女 202120081484==

曹雪芹借宝钗之口说出这篇少见的文章，一则以显示宝钗无书不读，再者也暗示自己博览群籍，同时也对那些自封的朱熹卫士予以调侃。可见曹雪芹即使开玩笑，也非闲笔，总有一定的用意。（详见注释）鉴于所要注释的词语性质不同，因此对注文的要求也有所不同。

Saying this rare writing through Precious Hairpin Marshgrass, on the one hand Cao Xueqin showed her strong love of reading as well as implied own extensive reading, and on the other, he played off those self-appointed guards of Zhu Xi. Obviously, his joking is not casual but absolutely with some profound meaning.(see annotations) The nature of words annotated is different, so the requirements for explanatory notes are different as well.--[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 02:41, 22 November 2021 (UTC)

==付红岩 Fù Hóngyán 英语语言文学（英美文学）女 202120081485==

其一，对于一般的疑难词语，重在疏通文意，多不引经据典，追根溯源。其二，对于成语、典故，则既要注明其出典，又要解释其本义，还要说明其引申义或比喻义。其三，对于各种名物（如建筑、服饰、官署、官职、琴棋书画、医卜星相等），则力求变专门术语为通俗语言，以利读者理解。

Firstly, as for normally confusing words, the emphasis is on clearing up the meaning of the text, as much quoting scripture and tracing the roots as possible. Secondly, for idioms and allusions, it is necessary to indicate their origins, explain their original meanings, and also include their derivative meanings or metaphorical meanings. Thirdly, for all kinds of physical objects (such as architecture, costumes, official offices, official positions, Four Arts( qin, chess, calligraphy and painting), medicine, divination and astrology, etc.), the attempt is to turn specialized terms into common language in order to facilitate readers’ understanding.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 11:24, 24 November 2021 (UTC)

Firstly, as for common confusing words, it should emphasize on clearing up the meaning of the text, as much quoting scripture and tracing the roots as possible. Secondly, for idioms and allusions, it is necessary to indicate their origins, explain their original meanings, and also include their derivative meanings or metaphorical meanings. Thirdly, for various technical terms of objects (such as architecture, costumes, official offices, official positions, Four Arts( qin, chess, calligraphy and painting), medicine, divination and astrology, etc.), the attempt is to turn specialized terms into common language in order to facilitate readers’ understanding.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 12:17, 28 November 2021 (UTC)

==付诗雨 Fù Shīyǔ 日语语言文学女 202120081486==

其四，对于历史名人，则注明其所在朝代、简历及突出事迹。对于传说人物，则注明其出处及相关故事。其五，对于珍禽异兽、奇花异卉等，则注明其出处来历、奇异之处及相关故事。

Fourthly, as for historical celebrities, their dynasties, resumes and outstanding deeds should be indicated. As for legendary figures, their sources and related stories should be indicated. Fifthly, as for rare birds and animals, unusual flowers and different plants, etc., their origins and histories, peculiar places and related stories should be indicated.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 14:36, 23 November 2021 (UTC)

Fourthly, as for historical celebrities, their dynasties, resumes and outstanding deeds should be indicated. As for legendary figures, their sources and related stories should be indicated. Fifthly, as for rare birds and fabulous beasts, unusual flowers and different plants, etc., their origins and histories, peculiarities and related stories should be indicated.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 15:50, 23 November 2021 (UTC)

==高蜜 Gāo Mì 翻译学女 202120081487==

其六，对于风俗、礼仪、节气等，则注明其形成沿革、具体内容。其七，对于谜语，则既要揭出谜底，又要解释谜语中的疑难词语、成语典故，还要说明谜底的根据。对于酒令，则要参照令谱，详述酒令的玩法及过程。

Sixthly, in terms of customs, etiquette and solar terms, its formation, development and content should be indicated. Seventhly, in terms of riddles, answers should be uncovered and an explanation is expected to be given to the answer as well as to difficult words, idioms and allusions in the riddle. Finally, in terms of drinking games, elaboration should be given on the rules and the process according to the instruction manual.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 15:51, 23 November 2021 (UTC)

Sixthly, in terms of customs, etiquette and solar terms, its formation, development and content should be indicated. Seventhly, in terms of riddles, answers should be uncovered and it is necessary to explain the difficult words and idioms in the riddle, and to explain the basis of the answer.Finally, in terms of drinking games, elaboration should be given on the rules and the process according to the instruction manual.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 05:45, 27 November 2021 (UTC)

==宫博雅 Gōng Bóyǎ 俄语语言文学女 202120081488==

其八，对于所引前人诗、词、曲、文等，皆要注明出处；诗、词、曲照录全文，文则节录相关的文字。其九，对于具有隐寓或暗示意味的诗、词、曲、文、成语、典故、谜语、酒令等，因其关系到故事情节的发展和人物性格、运命的描写，故除了作注释之外，还要揭示其隐藏的含义。总而言之，注文以释难为易、释疑为明为宗旨，以释义准确、释文简炼为目标。

Eighthly, reference to predecessors' poems, Ci, Qu, essay, etc., must indicate the source; Poems, Ci, Qu are transcribed without changing the original words, and the essay takes the relevant words. Ninthly, for poems, Ci, Qu, essay, idioms, allusions, riddles, drinkers’ wager game and so on with implicit or suggestive meaning, because they are related to the development of the story plot and the description of the character and fate, so in addition to making annotations, but also to reveal his hidden meaning. In a word, the annotations aim to explain the difficulty as easy, to explain the doubt as clear. Aim to explain the meaning accurately and explain the text concisely.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 05:32, 27 November 2021 (UTC)

Eight, all quotations from poems, lyrics, songs and essays should be attributed to the source; the poems, lyrics and songs should be reproduced in their entirety, while the essays should be excerpted from the relevant texts. Nine, for poems, lyrics, songs, texts, idioms, allusions, riddles, wine orders, etc., which have an implicit or suggestive meaning, as they relate to the development of the storyline and the description of the characters' personalities and fortunes. The commentary should reveal their hidden meanings in addition to annotations. All in all, the aim of the commentary is to explain the difficult for the easy and the doubtful for the clear, and to explain the meaning accurately and to explain the text concisely.--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 12:32, 28 November 2021 (UTC)

==何芩 Hé Qín 翻译学女 202120081489==

愿望虽然如此，但学力有限，经验欠缺，愿望能否实现，毫无把握。诚望方家指教，读者检验。

第一回甄士隐梦幻识通灵贾雨村风尘怀闺秀

Although I wish to do so, I am not sure whether my wish can be realized because of my limited learning and lack of experience.I hope that the readers will test it.

Chapter 1 Hidden Turth--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 12:33, 28 November 2021 (UTC)

Although I wish to do so, I am not sure whether the wish can come true with my limited ability and experience. Sincerely hope that other authors teach something and readers check it.

Chapter 1 Zhen Shiyin, in a vision, apprehends spirituality. Jia Yucun, in the windy and dusty world, cherishes fond thoughts of a beautiful maiden. --[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 07:21, 24 November 2021 (UTC)

==胡舒情 Hú Shūqíng 英语语言文学（语言学）女 202120081490==

此开卷第一回也。作者自云：曾历过一番梦幻之后，故将真事隐去，而借“通灵”之说，撰此《石头记》一书也，故曰“甄士隐”云云。但书中所记何事何人

This is the first chapter of the book. The author said that after going through the illusion, he prefered covering some truth and in virtue of mysticism wrote the novel ''The Story of the Stone''，so instead he used the name of Zhen Shiyin as a major speaker. But things and people noted in it--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 03:59, 23 November 2021 (UTC)

This is the first chapter of the book.Subsequent to the visions of a dream which he had，on some previous occasion，experienced，the writer personally relates，he designedly concealed the true circumstances，and borrowed the attributes of perception and spirituality to relate this story of the Record of the Stone. With this purpose，he made use of such designations as Chen Shih-yin and the like. What are，however，the events recorded in this work？--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 10:19, 24 November 2021 (UTC)

==黄锦云 Huáng Jǐnyún 英语语言文学（语言学）女 202120081491==

自己又云：“今风尘碌碌，一事无成。忽念及当日所有之女子，一一细考较去，觉其行止见识，皆出我之上；我堂堂须眉，诚不若彼裙钗：我实愧则有馀，悔又无益，大无可如何之日也。当此日，欲将已往所赖天恩祖德，锦衣纨袴之时，饫甘餍肥之日，背父兄教育之恩，负师友规训之德，以致今日一技无成、半生潦倒之罪，编述一集，以告天下：知我之负罪固多，然闺阁中历历有人，万不可因我之不肖，自护己短，一并使其泯灭也。

The author speaking for himself, goes on to explain, with the lack of success which attended every single concern, I suddenly bethought myself of the womankind of past ages. Passing one by one under a minute scrutiny, I felt that in action and in lore, one and all were far above me; that in spite of the majesty of my manliness, I could not, in point of fact, compare with these characters of the gentle sex. And my shame forsooth then knew no bounds; while regret, on the other hand, was of no avail, as there was not even a remote possibility of a day of remedy.On this very day it was that I became desirous to compile, in a connected form, for publication throughout the world, with a view to (universal) information, how that I bear inexorable and manifold retribution; inasmuch as what time, by the sustenance of the benevolence of Heaven, and the virtue of my ancestors, my apparel was rich and fine, and as what days my fare was savory and sumptuous, I disregarded the bounty of education and nurture of father and mother, and paid no heed to the virtue of precept and injunction of teachers and friends, with the result that I incurred the punishment, of failure recently in the least trifle, and the reckless waste of half my lifetime. There have been meanwhile, generation after generation, those in the inner chambers, the whole mass of whom could not, on any account, be, through my influence, allowed to fall into extinction, in order that I, unfilial as I have been, may have the means to screen my own shortcomings.--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 12:42, 22 November 2021 (UTC)

The author goes on to explain, with the lack of success which attended every single concern, I suddenly bethought myself of the womankind of past ages. Thinking of them one by one under a minute scrutiny, I felt that in action and in lore, one and all were far above me; that in spite of the majesty of my manliness, I could not, in point of fact, compare with these characters of the gentle sex. And my shame forsooth then knew no bounds; while regret, on the other hand, was of no avail, as there was not even a remote possibility of a day of remedy.On this very day it was that I became desirous to compile, in a connected form, for publication throughout the world, with a view to (universal) information, how that I bear inexorable and manifold retribution; inasmuch as what time, by the sustenance of the benevolence of Heaven, and the virtue of my ancestors, my apparel was rich and fine, and as what days my fare was savory and sumptuous, I disregarded the bounty of education and nurture of father and mother, and paid no heed to the virtue of precept and injunction of teachers and friends, with the result that I incurred the punishment, of failure recently in the least trifle, and the reckless waste of half my lifetime. There had been meanwhile, generation after generation, those in the inner chambers, the whole mass of whom could not, on any account, be, through my influence, allowed to fall into extinction, in order that I, unfilial as I have been, may have the means to hide my own shortcomings.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 14:34, 22 November 2021 (UTC)

==黄逸妍 Huáng Yìyán 外国语言学及应用语言学女 202120081492==

所以蓬牖茅椽，绳床瓦灶，并不足妨我襟怀；况那晨风夕月，阶柳庭花，更觉得润人笔墨。我虽不学无文，又何妨用假语村言敷演出来，亦可使闺阁昭传，复可破一时之闷，醒同人之目，不亦宜乎？”故曰“贾雨村”云云。

"Though my home is now a thatched cottage in which there are shabby windows, bed made of rope and earthen stove, all of these can not change my being broad and level. Besides, the morning breeze, the dew of night, the willows by me steps and the flowers in the yard inspired me to wield my pen. Though I have little learning and literary talent, it doesn't matter if I tell a tale in rustic language to record those lovely girls. This should help readers distract them from their worries. And that's the reason why I use the name Rainvillage Merchant."--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 13:27, 21 November 2021 (UTC)

"Though my home is now a thatched cottage in which there are shabby windows, bed made of rope and earthen stove, all of these can not change my being broad and level. Besides, the morning breeze, the dew of night, the willows by me steps and the flowers in the yard inspired me to wield my pen. Though I have little learning and literary talent, it doesn't matter if I tell a tale in rustic language to record those lovely girls. This should help readers distract them from their worries. And that's the reason why I use the name Jia Yucun."--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 14:19, 23 November 2021 (UTC)

==曾俊霖 Zēng Jùnlín 国别男 202120081478==

更于篇中间用“梦”、“幻”等字，却是此书本旨，兼寓提醒阅者之意。看官：你道此书从何而起？说来虽近荒唐，细玩颇有趣味。

In the middle of the article, the words "dream" and "fantasy" are the purpose of the book and the meaning of reminding readers. Reader: where did you start this book? Although it's absurd, it's fun to play.--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 13:21, 23 November 2021 (UTC)
In the middle of the article, the words "dream" and "fantasy" are the purpose of the book and the meaning of reminding readers. Reader: where did you start this book? Although it's absurd, it's fun to play.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:33, 24 November 2021 (UTC)Huang Zhuliang

==黄柱梁 Huáng Zhùliáng 国别男 202120081493==

却说那女娲氏炼石补天之时，于大荒山无稽崖，炼成高十二丈、见方二十四丈大的顽石三万六千五百零一块，那娲皇只用了三万六千五百块，单单剩下一块未用，弃在青埂峰下。谁知此石自经锻炼之后，灵性已通，自去自来，可大可小。因见众石俱得补天，独自己无才，不得入选，遂自怨自愧，日夜悲哀。一日，正当嗟悼之际，俄见一僧一道远远而来，生得骨格不凡，丰神迥异，来到这青埂峰下，席地坐谈。It is said that, once upon a time, when Nuwa was refining stones to mend the sky, she refined them into 36,501 pieces of hard stones 12-feet high and 24-feet square on the Wuji Cliff of the Da Huangshan Mountain. Numa, the creator of human beings in Chinese myth, only used 36,500 pieces, leaving only one unused and abandoned it under the Qinggeng Peak.Who knows, after the stone has been refined and created, its spirit has been passed. It can be big or small.Seeing that all the stones were able to mend the sky, he had no talent and could not be selected, so he complained and felt ashamed and mourned day and night. One day, at the time of mourning, he suddenly saw a monk and a Taoism priest with extraordinary personality coming from afar. They came to the Qinggeng Peak and sat on the ground to talk.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:34, 24 November 2021 (UTC)Huang Zhuliang

It is said that, once upon a time, when Nuwa(Goddesses of Sky-patching) was refining stones to mend the sky, she refined them into 36,501 pieces of hard stones 12-feet high and 24-feet square on the Wuji Cliff of the Da Huangshan Mountain. Numa, the creator of human beings in Chinese myth, only used 36,500 pieces, leaving only one unused and abandoned it under the Qinggeng Peak.Who knows, after the stone has been refined and created, it had its spirit, it moved freely and could be big or small.Seeing that all the stones were able to mend the sky, he had no talent and could not be selected, so he complained and felt ashamed and mourned day and night. One day, at the time of mourning, he suddenly saw a monk and a Taoism priest with extraordinary personality coming from afar. They came to the Qinggeng Peak and sat on the ground to talk.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 05:57, 26 November 2021 (UTC)

==金晓童 Jīn Xiǎotóng 202120081494==

见着这块鲜莹明洁的石头，且又缩成扇坠一般，甚属可爱。那僧托于掌上，笑道：“形体倒也是个灵物了，只是没有实在的好处。须得再镌上几个字，使人人见了，便知你是件奇物。

It was lovely to see this bright and clean stone shrinking like a fan. Resting on his palm, the monk smiled and said, "The body is a spiritual being, but it has no real benefit. Words had to be engraved so that everyone could see you and know that you were a wonder.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 15:01, 20 November 2021 (UTC)
Looking at this bright and clean stone shrinking like a fan, which is so lovely, with the stone on his palm the monk smiled and said, "Your body is a spiritual being, but ihas no real benefits. Words should be engraved so that everyone could see you and know that you are a wonder.--[[User:Kuang Yanli|Kuang Yanli]] ([[User talk:Kuang Yanli|talk]]) 11:42, 24 November 2021 (UTC)

==邝艳丽 Kuàng Yànl 英语语言文学（语言学）女 202120081495==

然后携你到那昌明隆盛之邦、诗礼簪缨之族、花柳繁华地、温柔富贵乡那里去走一遭。”石头听了大喜，因问：“不知可镌何字？携到何方？望乞明示。”那僧笑道：“你且莫问，日后自然明白。”
Then take you there, a city-state of prosperity, a family of scholar, a place of flowers and willows. After listening, Stone asked rejoicingly: “I do not know what word I can write? Where I will be taken to? I hope get your instruction.” The monk smiled, “You do not rush into answer, and you will know it some day.”--[[User:Kuang Yanli|Kuang Yanli]] ([[User talk:Kuang Yanli|talk]]) 11:24, 24 November 2021 (UTC)

Then I'll take you for a walk to the prosperous country, the family of poems, gifts and tassels, the prosperous place of flowers and willows, and the gentle and rich township. " The stone was overjoyed when he asked, "I don't know what word to engrave? Where to carry it? I hope to beg clearly." the monk smiled and said, “You do not rush into answer, and you will know it some day.”--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 14:54, 28 November 2021 (UTC)

==李爱璇 Lǐ Àixuán 英语语言文学（语言学）女 202120081496==

说毕，便袖了，同那道人飘然而去，竟不知投向何方。又不知过了几世几劫，因有个空空道人访道求仙，从这大荒山无稽崖青埂峰下经过，忽见一块大石，上面字迹分明，编述历历。空空道人乃从头一看，原来是无才补天，幻形入世，被那茫茫大士、渺渺真人携入红尘、引登彼岸的一块顽石：上面叙着堕落之乡、投胎之处，以及家庭琐事、闺阁闲情、诗词谜语，倒还全备。

Having concluded these words, he put the stone in his sleeve, and proceeded on his journey, in company with the Taoist priest. No one knows where he took the stone. Nor can it be known how many centuries and ages elapsed, before a Taoist priest, named K'ung K'ung, passed, during his researches after the eternal reason and his quest after immortality, by these Ta Huang Hills, Wu Ch'i cave and Ch'ing Keng Peak. Suddenly seeing a large stone, on the surface of which the handwriting on it is clear and the calendar is compiled, K'ung K'ung examined them from first to last. They, in fact, explained how that this stone had originally been devoid of the properties essential for the repairs to the heavens, how it would be transmuted into human form and introduced by Mang Mang the High Lord, and Miao Miao, the Divine, into the world of mortals, and how it would be led over the other bank (across the San Sara). On the surface, it describes the land of degeneration, the place of reincarnation, as well as family trivia, boudoir leisure, poetry, riddles, which could not be ascertained.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 04:54, 24 November 2021 (UTC)

Having concluded these words, he put the stone in his sleeve, and proceeded leisurely on his journey, in company with the Taoist priest. However, no one knew where he went. Nor can it be known how many centuries and ages elapsed, before a Taoist priest, K'ung K'ung by name, passed, during his researches after the eternal reason and his quest after immortality, by these Da Huang Hills, Wu Ch'i cave and Ch'ing Keng Peak. Suddenly perceiving a large block of stone, on the surface of which the traces of characters giving in a connected form, the various incidents of its fate could be clearly predicted. K'ung K'ung examined them from beginning to end. In fact, they explained how this block of worthless stone which had originally been devoid of the properties essential for the mending to the heavens, would be transmuted into human form and introduced by Mang Mang the High Lord, and Miao Miao, the Divine, into the world of mortals, and how it would be led over the other world (across the San Sara). On the surface, it recorded the spot of its degeneration and the place of its birth. The complete recording also included various family trifles, trivial affairs of young ladies, verses and riddles.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 06:17, 28 November 2021 (UTC)

==李瑞洋 Lǐ Ruìyáng 英语语言文学（英美文学）女 202120081497==

只是朝代年纪，失落无考。后面又有一偈云：无才可去补苍天，枉入红尘若许年。此系身前身后事，倩谁记去作奇传？

But the name of the dynasty and the year of the reign were obliterated and could not be confirmed. There was also a Buddhist verse following behind:
Lacking in virtues to mend the azure skies,
in vain I have been into the mortal world for many years.
These facts are of a former and after life,
but who will record a strange legend for me?--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 03:57, 24 November 2021 (UTC)

But the name of the dynasty and the year of the reign were obliterated and could not be confirmed. There was also a Buddhist verse following behind:
Lacking in virtues to mend the azure sky, nothing have I gained within the years spent in the secular world. All of these about my present life and afterlife, who would record them for me?--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 14:59, 26 November 2021 (UTC)

==李姗 Lǐ Shān 英语语言文学（英美文学）女 202120081498==

空空道人看了一回，晓得这石头有些来历，遂向石头说道：“石兄，你这一段故事，据你自己说来，有些趣味，故镌写在此，意欲闻世传奇。据我看来：第一件，无朝代年纪可考；第二件，并无大贤大忠理朝廷、治风俗的善政，其中只不过几个异样女子，或情或痴，或小才微善。我纵然抄去，也算不得一种奇书。”

As the Taoist priest named Kongkong once has examined the stone, he had some idea about the story on it, and then said to the stone, "Brother, maybe in your opinion, the story inscribed on you is of some interest so as to be kept here to win a fame throughout the world. But to my mind, it is far from a legend book to be transcribed. Firstly, there are hardly any clues about the time period of the background; secondly, no outstanding governance regarding politics and costumes has been achieved by great talents or loyal officials, and what it mainly narrates are merely several unusual women, some stuck in love, some boasting subtle intelligence and benevolence."--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 09:02, 21 November 2021 (UTC)

As the Taoist priest named Kongkong once has examined the stone, he knew that the stone had some history, and then said to the stone, "Brother, maybe in your opinion, the story inscribed on you is of some interest so as to be kept here to win a fame throughout the world. But to my mind, it is far from a legend book to be transcribed. Firstly, there are hardly any clues about the time period of the background; secondly, no outstanding governance regarding politics and costumes has been achieved by great talents or loyal officials, and what it mainly narrates are merely several unusual women, some stuck in love, some boasting subtle intelligence and benevolence."--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 03:05, 27 November 2021 (UTC)

==李双 Lǐ Shuāng 翻译学女 202120081499==

石头果然答道：“我师何必太痴？我想历来野史的朝代，无非假借汉、唐的名色；莫如我这石头所记，不借此套，只按自己的事体情理，反倒新鲜别致。况且那野史中，或讪谤君相，或贬人妻女，奸淫凶恶，不可胜数；更有一种风月笔墨，其淫秽污臭，最易坏人子弟。

The stone answered: “Why are you so stubborn? I think the dynasties of unofficial history are nothing more than under the guise of Han, Tang. They are not as good as the stories recorded by me, a stone, which don’t follow the convention but according to the real facts and therefore are more novel on the contrary. Moreover, those unofficial histories are either slandering the emperor and his subjects, or belittling other people’s wives and children. There are countless descriptions of ferocity and adultery which are the most likely to have a bad influence on the younger generation.”--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 10:54, 24 November 2021 (UTC)

The stone answered: “Why are you so stubborn? I think the dynasties recorded in the unofficial histories are nothing more than under the guise of Han and Tang Dynasty. They are not as good as the stories recorded by me, a stone, which don’t follow the convention but according to the real facts and therefore are more novel on the contrary. Besides, those unofficial histories are either slandering the emperor and his subjects, or belittling other people’s wives and children. There are countless descriptions of ferocity and adultery which are most likely to have a bad influence on the younger generation.” --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 11:10, 24 November 2021 (UTC)

==李文璇 Lǐ Wénxuán 英语语言文学（英美文学）女 202120081500==

至于才子佳人等书，则又开口文君，满篇子建，千部一腔，千人一面，且终不能不涉淫滥。在作者不过要写出自己的两首情诗艳赋来，故假捏出男女二人名姓；又必旁添一小人拨乱其间，如戏中小丑一般。更可厌者，之乎者也，非理即文，大不近情，自相矛盾。

As for the books about the talented and the beauties, they talked about Wen and Jun, the pages were also full of Zi and Jian. A thousand volumes present the same thing, and a thousand person are also in the same character. Moreover, they cannot avoid to some licentious things. The authors, who had to write several sentimental odes and elegant ballads, had falsely invented the names of both men and women, and also some bad guys who like a clown in a play made some troubles in there. As for the annoying men, they had nothing in their minds and talked about Li and Wen, which had no link with the targeted things and paradoxical in the whole.--[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 00:53, 22 November 2021 (UTC)
As for books related to talented scholars and beautiful ladies, he also talked about Wenjun, who is good at articles and is capricious, but he could not avoid prostitution in the end. The author just wants to write two of his own love poems, so he falsely pinches out the names of men and women; he must add a little person to make trouble in the meantime, like a clown in a play. The more annoying, the more it is, the unreasonable is the literary, the most unkind, self-contradictory.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 03:24, 24 November 2021 (UTC)

==李雯 Lǐ Wén 英语语言文学（英美文学）女 202120081501==

竟不如我这半世亲见亲闻的几个女子，虽不敢说强似前代书中所有之人，但观其事迹原委，亦可消愁破闷；至于几首歪诗，也可以喷饭供酒。其间离合悲欢，兴衰际遇，俱是按迹循踪，不敢稍加穿凿，至失其真。只愿世人当那醉馀睡醒之时，或避事消愁之际，把此一玩，不但是洗旧翻新，却也省了些寿命筋力，不更去谋虚逐妄了。
It’s not as good as the few women I’ve seen and heard about in this half of my life. Although I dare not say that she is better than all the people in the books of the previous generations. Looking at their deeds, you can also relieve your sorrow and boredom. As for a few poor poems, you can also taste them while eating and drinking.The joys and sorrows, the ups and downs all follow the traces, daring not to lose the truth. I only hope that when the world is awake, or when avoiding troubles and sorrows ,they can enjoy it, not only to renovate, but also to save some lifespan and energy, not to seek falsehood.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 03:15, 24 November 2021 (UTC)

I am not as good as the women I have seen and heard in my life. Though I cannot say that they are as good as all the people in the books of previous generations, I can relieve my sorrow and despair by watching their deeds. As for a few crooked poems, you can also spray rice for wine. During the separation of joys and sorrows, ups and downs, are all traced, dare not slightly cut, to lose its true. I only hope that when people wake up from their drunkenness, or when they are relieved of their sorrow, they will not only wash the old and renew it, but also save some strength of life, so as not to seek for false things.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 04:39, 24 November 2021 (UTC)

==李新星 Lǐ Xīnxīng 亚非语言文学女 202120081503==

我师意为如何？”空空道人听如此说，思忖半晌，将这《石头记》再检阅一遍。因见上面大旨不过谈情，亦只是实录其事，绝无伤时诲淫之病，方从头至尾抄写回来，闻世传奇。
What do I mean?" Empty Taoist listen to say so, ponder a long time, will this "stone" review again. Seeing that the message above was only a talk of love, and only a record of it, without suffering from the disease of lewdness, I copied it back from beginning to end and heard the legend of the world.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 04:38, 24 November 2021 (UTC)

What do I mean? " After hearing this, Taoist Kongkong thought for a long time and reviewed the stone story again. Seeing that the above general purpose is nothing but romance, it is only a factual record of its affairs, and there is no disease of obscenity at the time of injury, so I copied it back from beginning to end and heard the legend of the world.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 04:35, 24 November 2021 (UTC)

==李怡 Lǐ Yí 法语语言文学女 202120081504==

从此空空道人因空见色，由色生情，传情入色，自色悟空，遂改名情僧，改《石头记》为《情僧录》。东鲁孔梅溪题曰《风月宝鉴》。后因曹雪芹于悼红轩中披阅十载，增删五次，纂成目录，分出章回，又题曰《金陵十二钗》，并题一绝。
Since then empty Taoist empty because of empty see color, from color feeling, feeling into color, since color wukong, then changed the name of the monk, "stone" for "love monk record". Kong Meixi of The Eastern Lu dynasty wrote the book Fengyue Bao Jian. After cao Xueqin in mourning red xuan read ten years, add and delete five times, compiled into a directory, a chapter back, and the title yue ''Jinling twelve Hairpin'', and a must.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 04:31, 24 November 2021 (UTC)

Since then Empty Taoist saw form through emptiness, generated emotions due to form, into which emptiness was stilled and epiphany was revealed, he then changed his epithet into Monk in Love, and changed ''The story of the Stone'' into ''Record of Monk in Love'', which was called ''Catalogue of Chinese Ancient Romance'' by Kong Meixi of The Eastern Lu dynasty. Afterwards Cao Xueqin read and amended it for ten years, revised and polished it for five times, and then compiled it into a directory with chapters and sections. Finally he entitled it ''The Twelve Flowers in Jinlin'' attached with a Chinese quatrain.--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 04:55, 24 November 2021 (UTC)

==刘沛婷 Liú Pèitíng 英语语言文学（英美文学）女 202120081505==

即此便是《石头记》的缘起。诗云：满纸荒唐言，一把辛酸泪。都云作者痴，谁解其中味?

This was the origin of ''The Story of The Stone''. A poem once said, “the whole novel is full of absurd words, as well as bitter tears. People all consider the author crazy, but is there anyone who knows its true meaning？--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 07:22, 23 November 2021 (UTC)

This is the origin of ''The Story of the Stone''. The poem says: The pages were full of idle words which was penned with hot and bitter tears; All men call the author fool, but no one understood his secret message.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 08:25, 23 November 2021 (UTC)

==刘胜楠 Liú Shèngnán 翻译学女 202120081506==

《石头记》缘起既明，正不知那石头上面记着何人何事？看官请听。按那石上书云：当日地陷东南，这东南有个姑苏城，城中阊门最是红尘中一二等富贵风流之地。

Now that the origin of the stone is clear, let us see what was written on the stone. Dear readers, please listen. Long ago, the earth dipped downwards in the southeast where there was a city named Gusu; and the quarter around Changmen Gate of Gusu was one of the most fashionable centres of wealth and nobility in the world of men. --[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 02:10, 23 November 2021 (UTC)

The origin of "The Story of the Stone" was clear, but did you know who or what was written on the stone? Please listen to me and go on. According to the record on the stone: One day, there was a subsidence in southeast and there was Gusu City. In the city, the quarter around Changmen Gate was one of the most fashionable centres of wealth and nobility in the world of men. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 03:13, 23 November 2021 (UTC)Liu Wei

==刘薇 Liú Wēi 国别女 202120081507==

这阊门外有个十里街，街内有个仁清巷，巷内有个古庙，因地方狭窄，人皆呼作“葫芦庙”。庙旁住着一家乡宦，姓甄名费，字士隐；嫡妻封氏，性情贤淑，深明礼义。家中虽不甚富贵，然本地也推他为望族了。

Outside the city of Changmen gate, there was a Shili street and a Renqing lane was on the street. In the Renqing lane, there was an ancient temple called "Hulu temple" owing to it`s narrow location. Next to the temple lived a hometown official named Zhen Fei, courtesy named Shi Yin; his legal wife, surnamed Feng, was a virtuous person with a deep sense of courtesy and righteousness. Although the family was not very rich, the local people also thought that he was a prominent family. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 14:02, 21 November 2021 (UTC)Liu Wei

Outside the Changmen gate was the Shili street and the Renqing lane, inside which was an ancient temple, called the "Gourd temple" for its narrow space. Next to the temple lived a retired official named Zhen Fei, whose courtesy name was Shi Yin; his legal wife Mrs. Feng was a virtuous person with a deep awareness of courtesy and righteousness. Although the family was not very rich, the locals also regarded him as a noble man.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 15:19, 22 November 2021 (UTC)

==刘晓 Liú Xiǎo 英语语言文学（英美文学）女 202120081508==

因这甄士隐禀性恬淡，不以功名为念，每日只以观花种竹、酌酒吟诗为乐，倒是神仙一流人物。只是一件不足：年过半百，膝下无儿；只有一女，乳名英莲，年方三岁。一日炎夏永昼，士隐于书房闲坐，手倦抛书，伏几盹睡，不觉矇眬中走至一处，不辨是何地方。

Hidden Truth had a tranquil mind, indifferent to fame or gain. The only fun in every day life was enjoying beautiful flowers and planting bamboo, drinking nectared wine and reciting poetry. What a fairy-like figure! There was only one pity, that is, though in his fifty years old, he had no son nut only one three-year-old daughter, named Pity Zhen. One day in the hot summer, Hidden Truth was sitting idly in his study. Tired, he threw away his book and fell asleep at his desk, drifting to a place he could not tell.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 03:19, 21 November 2021 (UTC)

Zhen Shiyin had a tranquil mind, indifferent to fame or gain. The only fun in every day life was enjoying beautiful flowers and planting bamboo, drinking nectared wine and reciting poetry. What a fairy-like figure! But there was one pity, that is, though in his fifty years old, he had no son nut only one three-year-old daughter, named Yinglian. One day in the hot summer, Shenyin was sitting idly in his study. He was so tired that he threw away his book and fell asleep at his desk, drifting to a place he could not tell.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 05:12, 23 November 2021 (UTC)

==刘越 Liú Yuè 亚非语言文学女 202120081509==

忽见那厢来了一僧一道，且行且谈。只听道人问道：“你携了此物，意欲何往？”那僧笑道：“你放心。如今现有一段风流公案，正该了结，这一干风流冤家，尚未投胎人世。

Unexpectedly he espied， in the opposite direction， two priests coming towards him： the one a Buddhist， the other a Taoist. As they advanced they kept up the conversation in which they were engaged. "Whither do you purpose taking the object you have brought away？" he heard the Taoist inquire. To this question the Buddhist replied with a smile： "Set your mind at ease，" he said； "there's now in maturity a plot of a general character involving mundane pleasures， which will presently come to a denouement. The whole number of the votaries of voluptuousness have， as yet， not been quickened or entered the world.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 05:07, 23 November 2021 (UTC)

Unexpectedly he espied, from the opposite direction, A monk and a Taoist coming up to him. As they advanced, they kept up the conversation in which they were engaged. "Whither do you purpose taking the thing you have brought away？" He heard the Taoist inquire. The Buddhist replied with a smile: "Set your mind at ease. There's now a case of romantic affairs, which should presently come to a denouement. The whole number of the votaries of voluptuousness involved in have not been reincarnated.--[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:31, 24 November 2021 (UTC)

==刘运心 Liú Yùnxīn 英语语言文学（英美文学）女 202120081510==

趁此机会，就将此物夹带于中，使他去经历经历。”那道人道：“原来近日风流冤家又将造劫历世，但不知起于何处，落于何方？”那僧道：“此事说来好笑。

Taking this opportunity, we can mingle it in them and let it experience the life on earth." The Taoist said: "So those debtors of love affairs will be reincarnated and then suffer on earth. But from which place will the reincarnation start and in which direction will them be placed still remain unsettled." The monk said: "It's a funny story. --[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:28, 24 November 2021 (UTC)

Taking this opportunity, we can carry it away and let it experience the life on earth. ”The Taoist priest said: "The debtors of love affairs will be reincarnated and then suffer on earth recently. But it' s unknown that from when the story started and to where will it go.“ The monk said: "It's a funny story....-- --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 08:23, 28 November 2021 (UTC)

==罗安怡 Luó Ānyí 英语语言文学（英美文学）女 202120081511==

只因当年这个石头，娲皇未用，自己却也落得逍遥自在，各处去游玩。一日来到警幻仙子处，那仙子知他有些来历，因留他在赤霞宫中，名他为赤霞宫神瑛侍者。他却常在西方灵河岸上行走，看见那灵河岸上三生石畔有棵绛珠仙草，十分娇娜可爱，遂日以甘露灌溉，这绛珠草始得久延岁月。

This stone have not been used by The Empress Nu Wo. Thus It used to be free to roam on the heavens until one day he came to the Fairy of Wonders, who knew his special background. So she kept him in her palace and gave him the name by the Divine Eunuch of the Palace. He often walked along the bank of the Spirit River in the West where he saw a delicate and lovely flower on the bank of the Three Living Stones. Being struck with the great beauty of this flower, the stone remained there, tending its protegee with the most loving care, and daily moistening its roots with the choicest nectar of the sky. Yielding to the influence of disinterested love, the flower lived a longer life. --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 07:32, 28 November 2021 (UTC)

Because this stone in that age hasn‘t been used by a goddess in Chinese mythology，he could be careless and can go to visit many places for fun.One day，he come to the Fairy of Wonders who knew his special background. So she kept him in her palace and gave him the name by the Divine Eunuch of the Palace.But he always walks by the bank of the Spirit River.One day，he saw a fairy grass beside the Three Living Stones on the bank of the river，which is cute and delicate，so he irrigated it day by day，making it living longer.--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:31, 28 November 2021 (UTC)

==罗曦 Luó Xī 英语语言文学（英美文学）女 202120081512==

后来既受天地精华，复得甘露滋养，遂脱了草木之胎，幻化人形，仅仅修成女体，终日游于离恨天外，饥餐秘情果，渴饮灌愁水。只因尚未酬报灌溉之德，故甚至五内郁结着一段缠绵不尽之意。常说：‘自己受了他雨露之惠，我并无此水可还。
Afterwards，because of the essence of the nature and the nutrients of the dew，it gradually got rid of itself from the trees and become a human-being，but only can become a female，meandering outside all day long，when feeling hungry，she would eat fruits，and when feeling thirsty，she would drink water.The reason for her lingering emotions is that she haven‘t showed her gratitude to her benefactors.She always said that：“I was benefited from his dew，but I can‘t bring back a report.”--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:21, 28 November 2021 (UTC)--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:21, 28 November 2021 (UTC)

==马新 Mǎ Xīn 外国语言学及应用语言学女 202120081513==

他若下世为人，我也同去走一遭，但把我一生所有的眼泪还他，也还得过了。’因此一事，就勾出多少风流冤家都要下凡，造历幻缘，那绛珠仙草也在其中。今日这石正该下世，我来特地将他仍带到警幻仙子案前，给他挂了号，同这些情鬼下凡，一了此案。”

If he could be reincarnated as human in the next life, I would also go with him but only in this time return all the sorrows to him, which can let me go through the life. “For this reason, how many pretty teases have to descend to the world suffering the illusory fates, and the Crimson Pearl Flower is also among them. Today, this stone is about to be born, so I comes here specially to bring him to the court of Fairy Maiden Jinhuan, registering him and letting him go down to the earth with ghosts in order to settle the case.”--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 12:37, 24 November 2021 (UTC)

If he could be reincarnated as human in the next life, I would go with him, but I should also return all the sorrows in this time to him, which can enable me to go through the life. "For this reason, lots of pretty teases have to descend to the world suffering the illusory destiny, and that Crimson Pearl Flower is also amomg them. Today this jade is about to be born, so I come here specially to take him to the court of Fairy Maiden Jinhuan, endowing him with a registration and letting him go down to the earth with those sentimental ghosts so as to settle the case.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 15:16, 27 November 2021 (UTC)

==毛雅文 Máo Yǎwén 英语语言文学（英美文学）女 202120081514==

那道人道：“果是好笑，从来不闻有‘还泪’之说。趁此，你我何不也下世度脱几个，岂不是一场功德？”那僧道：“正合吾意。你且同我到警幻仙子宫中，将这蠢物交割清楚，待这一干风流孽鬼下世，你我再去。如今有一半落尘，然犹未全集。”

The Taoist priest says:"It's really ridiculous. I have never heard of the saying of 'returning tears'. We can also take this opportunity to release several souls from purgatory (help several souls of the decease get rid of worldly sufferings). Isn't it a merit?" The monk replies:"It's exactly what I am hoping for. You and I are going to the palace of the fairy maiden Jing Huan, and to deliver such a jade and figure it out. When these dissolute and sinful evils all pass away, we will go to the afterlife. Half of them have fallen into the earthly world, but they have not yet gathered completely."--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 15:04, 27 November 2021 (UTC)

The Taoist priest says:"It's really ridiculous. I have never heard of the saying of 'returning tears'. We can also take this opportunity to release several souls from purgatory (help several souls of the decease get rid of worldly sufferings). Isn't it a merit?" The monk replies:"It's exactly what I am hoping for. You and I will go the palace of the fairy maiden Jing Huan, and to deliver such a jade and figure it out. When these dissolute and sinful evils all pass away, we will go to the afterlife. Half of them have fallen into the earthly world, but they have not yet gathered completely."--[[User:Mao You|Mao You]] ([[User talk:Mao You|talk]]) 06:56, 23 November 2021 (UTC)

==毛优 Máo Yōu 俄语语言文学女 202120081515==

道人道：“既如此，便随你去来。”却说甄士隐俱听得明白，遂不禁上前施礼，笑问道：“二位仙师请了。”那僧、道也忙答礼相问。

The Taoist said, "In that case, let's go with you." Then Hidden Truth heard and understood, so he could not help but go forward to salute, smiling and saying, " Please, distinguished masters." The monk and the Taoist also replied with manners.

The Taoist said, "In that case, let's go with you." Then Hidden Truth heard and understood, so he could not help but go forward to salute, smiling and saying, " Please, distinguished masters." The monk and the Taoist also immediately replied with manners.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 10:50, 24 November 2021 (UTC)

==牟一心 Móu Yīxīn 英语语言文学（英美文学）女 202120081516==

士隐因说道：“适闻仙师所谈因果，实人世罕闻者。但弟子愚拙，不能洞悉明白。若蒙大开痴顽，备细一闻，弟子洗耳谛听，稍能警省，亦可免沉沦之苦了。”

Hidden Truth said: "What you master talked about the cause and effect is definitely rare in the world. But I am stupid and can't fully understand it. If you can explain it for me to get rid of infatuation and stubbornness, I will listen to you carefully and then take warning from it, avoiding the suffering of enthrallment."--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 08:01, 21 November 2021 (UTC)

Hidden Truth then said, "I have just heard you master's words about karma, a truly rare insight in the world. But I am too ignorant to understand it. If I could be enlightened by you two to get rid of infatuation and stubbornness, I would certainly listen carefully to all that you say and then take warning from it, avoiding the suffering of enthrallment."--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 07:54, 22 November 2021 (UTC)

==彭瑞雪 Péng Ruìxuě 法语语言文学女 202120081517==

二仙笑道：“此乃玄机，不可预泄。到那时只不要忘了我二人，便可跳出火坑矣。”士隐听了，不便再问，因笑道：“玄机固不可泄露，但适云‘蠢物’，不知为何？或可得见否？”那僧说：“若问此物，倒有一面之缘。”

The two immortals laughed and said, "It is something metaphysical and cannot be divulged in advance. At that time, just don't forget the two of us, and you will be free from your predicament." When Shi Yin heard this, he stopped pursuing the matter. He laughed and said, "Of course the mystery must not be divulged, but I don't quite understand what the 'stupid thing' is that you just mentioned. Perhaps I have a chance to see it?" The monk said, "This thing you are asking about, you do have the fortune to see it.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 07:39, 22 November 2021 (UTC)

The two immortals laughed and said, "It is metaphysical and cannot be divulged in advance. At that time, if you don't forget two of us, and you will be free from your predicament." When Shi Yin heard this, he stopped pursuing the matter. He laughed and said, "Of course the mystery must not be divulged, but I don't quite understand what the 'stupid thing' is that you just mentioned. Perhaps I have a chance to see it?" The monk said, "This thing you are asking about, you do have the fortune to see it.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 06:17, 29 November 2021 (UTC)

==秦建安 Qín Jiànān 外国语言学及应用语言学女 202120081518==

说着取出，递与士隐。士隐接了看时，原来是块鲜明美玉，上面字迹分明，镌着“通灵宝玉”四字，后面还有几行小字。正欲细看时，那僧便说已到幻境，就强从手中夺了去。

He said and took it out to Hidden Truth. ShiYin received it and found it a bright beautiful jade in which there were four clear characters:Tong Ling Bao Yu followes by several lines of words.When Hidden Truth craved for a careful look, that monk said that he had reached the illusion, so he snatched it from ShiYin's hand.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 02:57, 21 November 2021 (UTC)

Then he said as he took it out and handed it to Hidden Truth. Hidden Truth took a look, and it turned out to be a piece of bright beautiful jade, with clear writing above, engraved with the “Tongling jade”. There were a few lines of small characters behind. When he was about to take a closer look, the monk said he had reached the Illusory Land and snatched the jade from his hands.--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 01:47, 22 November 2021 (UTC)

==邱婷婷 Qiū Tíngtíng 英语语言文学（语言学）女 202120081519==

和那道人竟过了一座大石牌坊，上面大书四字，乃是“太虚幻境”。两边又有一副对联道：假作真时真亦假，无为有处有还无。士隐意欲也跟着过去，方举步时，忽听一声霹雳，若山崩地陷。

And with that Taoist priest actually passed a large stone archway, above which was engraved four big words, is “ Illusory Land of Great Void ”.On both sides there was a pair of couplets: If false is taken as the truth, then truth is said to be lieing , when nothing is taken as being, then being itself is turned into nothing. Hidden Truth also wanted to pass the big stone archway, but the moment he was about to raise his foot, he heard a crack of thunder which sounded as if the hills were rending asunder and the earth falling in.--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 02:52, 21 November 2021 (UTC)

And that Taoist passed a large stone pagoda, written on it four big words, is "Taixu fantasy realm". On both sides, there is a couplet saying: "Falsehood is true when it is true, and there is nothing where there is nothing". Hidden Truth also wanted to follow, when just ready to raise his feet, he heard a thunderbolt all of a sudden, as if a landslide happened.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 02:48, 21 November 2021 (UTC)

==饶金盈 Ráo Jīnyíng 英语语言文学（语言学）女 202120081520==

士隐大叫一声，定睛看时，只见烈日炎炎，芭蕉冉冉，梦中之事便忘了一半。又见奶母抱了英莲走来。士隐见女儿越发生得粉装玉琢，乖觉可喜，便伸手接来，抱在怀中，斗他玩耍一会。

Hidden Truth cried out, and when he fixed his eyes, only seeing the sun is shining, the weather is bright, and the plantains are flourishing, and then he forgot half of his dream. Later, the lactating mother coming with Pity Zhen in her arms. When Hidden Truth noted that his daughter was becoming more and more beautiful and cute, he reached out and took her in his arms, and teased her for a while.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 02:43, 21 November 2021 (UTC)

Hidden Truth cried out, fixing his eyes on the blazing sun and supplely drooping banana leaves, only to be oblivious to half of his dream. Then the wet nurse came over with Pity Zhen in her arms. Hidden Truth perceived that his daughter became so fair and lovely that he couldn’t wait to cradle her in his arms to amuse her.--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 05:48, 21 November 2021 (UTC)

== Headline text ==
==石丽青 Shí Lìqīng 英语语言文学（英美文学）女 202120081521==

又带至街前，看那过会的热闹。方欲进来时，只见从那边来了一僧一道：那僧癞头跣足，那道跛足蓬头，疯疯癫癫，挥霍谈笑而至。及到了他门前，看见士隐抱着英莲，那僧便大哭起来，又向士隐道：“施主，你把这有命无运、累及爹娘之物抱在怀内作甚？”

Hidden Truth then took his lovely daughter out into the street to see the lively meeting. When he was about to enter the door, he saw a monk and a Taoist coming from the other side: the monk had ringworm on his head and no shoes or socks on his feet; the Taoist priest was characterized by lameness and untidy hair. They came over, crazy, talking and laughing. When they got to Hidden Truth’s door, seeing him holding Pity Zhen in his arms. The monk began to cry and said to Hidden Truth, “ Benefactor, why did you cradle such an ill-fated and encumbering child in your arms？”--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 01:35, 21 November 2021 (UTC)

Shiyin then took his lovely daughter to the street to see the lively agora. When he was about to enter the door, he saw a monk and a Taoist priest coming from the other side: the monk had ringworm on his head and no shoes or socks on his feet; the Taoist priest was characterized by lameness and untidy hair. They acted like a lunatic and came over,talking and laughing. When they got to Shiyin’s door, seeing him holding Yinglian in his arms. The monk began to cry and said to Shiyin, “ Benefactor, why did you cradle such an ill-fated and encumbering child in your arms？”--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 06:06, 21 November 2021 (UTC)

==孙雅诗 Sūn Yǎshī 外国语言学及应用语言学女 202120081522==

士隐听了，知是疯话，也不睬他。那僧还说：“舍我罢，舍我罢。”士隐不耐烦，便抱着女儿转身。

After listening to him,Shiyin knew that it's crazy words and ignored him.But the monk also said:"Give her to me,give her to me." Shiyin was impatient,so he held his daughter and turned to leave.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 05:59, 21 November 2021 (UTC)

After listening to him, Hidden Truth knew that it was lunatic ravings and ignored him. But the monk complemented:"Give her to me, give her to me." Hidden Truth got impatient, so he embraced his daughter and turned around. --[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 12:14, 23 November 2021 (UTC)

==王李菲 Wáng Lǐfēi 英语语言文学（英美文学）女 202120081523==

才要进去，那僧乃指着他大笑，口内念了四句言词，道是：惯养娇生笑你痴，菱花空对雪澌澌。好防佳节元宵后，便是烟消火灭时。

When he was about to get in, the monk pointed at him and laughed, mumbling four sentences, which mean “how crazy that you pamper your daughter like this, (see you embrace Yinglian), just like the summer lotus are exposed to the winter snow. Beware of the days after the Lantern Festival, then there is a fire to vanish everything.”--[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 03:03, 21 November 2021 (UTC)
When he wanted to go in, the monk pointed at him and laughed, saying…--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 06:56, 24 November 2021 (UTC)

==王逸凡 Wáng Yìfán 亚非语言文学女 202120081524==

士隐听得明白，心下犹豫，意欲问他来历，只听道人说道：“你我不必同行，就此分手，各干营生去罢。三劫后，我在北邙山等你，会齐了，同往太虚幻境销号。”那僧道：“最妙，最妙。”
Shi Yin understood and hesitated, intending to ask him where he came from. The Taoist said, "You and I don't need to go together. Three days later, I wait for you in north mangshan, meet together, with the imaginary land sales number." The monk said, "The best, the best."--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 06:44, 24 November 2021 (UTC)

Shiyin understood,hesitated in his heart,and wanted to ask him where he came from.He only heard the Taoist say: "You and I don't have to go together, just break up and go to work. After the Three Tribulations, I will wait for you in Beimanshan,nnd go to the Tai Unreal Realm to sell the number." The monk said: "The most wonderful, the most wonderful."--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 13:40, 28 November 2021 (UTC)

==王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525==

说毕，二人一去，再不见个踪影了。士隐心中此时自忖：“这两个人必有来历，很该问他一问，如今后悔却已晚了。”这士隐正在痴想，忽见隔壁葫芦庙内寄居的一个穷儒，姓贾名化、表字时飞、别号雨村的走来。

After that,the two went away,and they were nowhere to be seen.Shiyin thought to himself at this moment: "These two people must have a history.It's time to ask him,but now it's too late to regret." Shiyin was thinking about it,but suddenly saw a poor scholar living in the Hulu temple next door whose first name is Jia,last name hua,Courtesy name Shifei,and another name Yucun came.--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 13:37, 28 November 2021 (UTC)

After saying that, the two went away, and there was no sign of them anymore. Shiyin thought to himself at this moment: "These two people surely had some backgrounds. I should have asked him, but it was too late to regret now." Shiyin was daydreaming, but suddenly saw a poor scholar living in the Hulu temple next door coming up. His first name is hua, last name is jia, secondary personal name is Shifei, and another name is Rainvillage Merchant.--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 14:46, 28 November 2021 (UTC)

==卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526==

这贾雨村原系湖州人氏，也是诗书仕宦之族。因他生于末世，父母祖宗根基已尽，人口衰丧，只剩得他一身一口。在家乡无益，因进京求取功名，再整基业。

Rainvillage Merchant was born in Huzhou and came from a family of Confucian scholars and officials. Because he was born in last phase of age, the roots of his ancestors had died out. Family declined, and left him alone. He found no benefit in hometown, so he went to Beijing to strive for fame and tried to make another solid foundation for family.--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 03:10, 21 November 2021 (UTC)

Jia Yucun came from Huzhou and was born in a family of scholars and officials. However, because he was born in the last phase of the age, the root of his ancestors had died out and family declined, leaving him alone in the world. He found no benefit in hometown, so he went to Beijing to strive for success and fame and tried to make the revitalization of his family.--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 04:46, 21 November 2021 (UTC)

==魏楚璇 Wèi Chǔxuán 英语语言文学（英美文学）女 202120081527==

自前岁来此，又淹蹇住了，暂寄庙中安身，每日卖文作字为生，故士隐常与他交接。当下雨村见了士隐，忙施礼陪笑道：“老先生倚门伫望，敢街市上有甚新闻么？”士隐笑道：“非也。适因小女啼哭，引他出来作耍。正是无聊的很，贾兄来得正好，请入小斋，彼此俱可消此永昼。”

Since arriving in Beijing the year before last, Jia Yuchun had led a hard life, living only in a temple. He wrote poems and articles in exchange for money every day, so Shiyin often often met with him. Once Yucun saw Shiyin, hurriedly saluted and said with a smile, " Sir, you are leaning on the door and looking at something. Is there any news in the market?" Shiyin smiled and said, "No. Just because my little girl cried, so I took her out to play. I am so bored now and you are so nice to appear in time. Please come into my study with me, so that we can both kill the boring time." --[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 03:35, 21 November 2021 (UTC)

Since arriving in Beijing the year before last, Jia Yuchun found himself in difficult conditions and desperate straits. He lived only in a temple and made a living by writing in exchange for money every day, so Shiyin often met with him. At that moment, Yucun saw Shiyin, hurriedly saluted and said with smile, " An old gentleman as you, leaning on the door and looking at something, I wander that is there any news in the street?" Shiyin smiled and said, "Hardly, just because my little girl cried, so I take her out to play. I am so bored now and you‘ve come just at the right moment. Please come into my study, so that we can spend the long day together."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 14:13, 23 November 2021 (UTC)

==魏兆妍 Wèi Zhàoyán 英语语言文学（英美文学）女 202120081528==

说着，便令人送女儿进去。自携了雨村来至书房中，小童献茶。方谈得三五句话，忽家人飞报：“严老爷来拜。”

While he was talking, he asked someone to take his daughter back to her room. Then he took Yucun to his study, and a child offered a cup of tea for each of them. But just said a few words, suddenly the family member came quickly to say that "Master Yan came to visit."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 07:30, 23 November 2021 (UTC)

While talking, he asked someone to take his daughter back to her room. Then he took Yucun to his study, and a child offered a cup of tea for each of them. But just said a few words, suddenly the family member came quickly to say that "Master Yan came to visit." --[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 14:01, 24 November 2021 (UTC)

==吴婧悦 Wú Jìngyuè 俄语语言文学女 202120081529==

士隐慌忙起身谢道：“恕诓驾之罪。且请略坐，弟即来奉陪。”雨村起身也让道：“老先生请便。晚生乃常造之客，稍候何妨！”说着，士隐已出前厅去了。

Shiying stood up hurriedly and said, " Excuse me.Please sit for a moment first, and I will entertain you at once." Yucun also stood up and answered:" Old gentleman, you go. I often come to you here as a guest, wait a little while is not the matter!" Said, Shiying had walked out of the guest room.--[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 02:51, 21 November 2021 (UTC)
Shiyin hurriedly got up and thanked, "excuse the crime of cheating driving. Please sit down and my brother will accompany you." Yucun got up and said, "please help yourself, sir. My late life is a regular guest. Why not wait a minute!" said Shiyin, who had left the front hall.--[[User:Wu Yinghong|Wu Yinghong]] ([[User talk:Wu Yinghong|talk]]) 13:44, 22 November 2021 (UTC)

==吴映红 Wú Yìnghóng 日语语言文学女 202120081530==

这里雨村且翻弄诗籍解闷，忽听得窗外有女子嗽声。雨村遂起身往外一看，原来是一个丫鬟在那里掐花儿：生的仪容不俗，眉目清秀，虽无十分姿色，却也有动人之处。雨村不觉看得呆了。那甄家丫鬟掐了花儿，方欲走时，猛抬头见窗内有人：敝巾旧服，虽是贫窘，然生得腰圆背厚，面阔口方，更兼剑眉星眼，直鼻方腮。
Here in the rain village, I turned to poetry books to relieve my boredom. Suddenly I heard a woman coughing outside the window. Yucun then got up and looked out. It turned out that it was a servant girl pinching flowers there: Sheng's appearance was not vulgar and his eyebrows were beautiful. Although he was not very beautiful, he was also moving. Yucun was stunned. The Zhen servant girl pinched the flowers. When Fang was about to leave, she suddenly looked up and saw someone in the window: Although I was poor and embarrassed, I had a round waist, thick back, wide face and square mouth. I also had sword eyebrows, star eyes, straight nose and square cheeks.

Yuncun was reading poems to relieve his boredom, suddenly hearing a girl outside the window coughing. Yucun stood up and found a housemaid picking flowers: she was of good appearance and pretty features. Although she was not perfect, she had something touching. Yucun felt stunned. The girl had pinched the flowers and was about to leave when she suddenly raised her head and saw someone in the window. In rags, he had a round waist and a thick back, a wide face and a square mouth, with a sword eyebrow and star eyes, a straight nose and a square cheek.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 10:14, 24 November 2021 (UTC)

==肖毅瑶 Xiāo Yìyáo 英语语言文学（英美文学）女 202120081531==

这丫鬟忙转身回避，心下自想：“这人生的这样雄壮，却又这样褴褛。我家并无这样贫窘亲友，想他定是主人常说的什么贾雨村了。怪道又说他必非久困之人，每每有意帮助周济他，只是没什么机会。”如此一想，不免又回头一两次。雨村见他回头，便以为这女子心中有意于他，遂狂喜不禁，自谓此女子必是个巨眼英豪，风尘中之知己。
The housemaid turned away quickly and said to herself:” the man is so grand and ragged. I don’t have such deprived friends and relatives, thus he must be Rain Village Merchant that the master has mentioned frequently. It’s said that he will not be trapped in poverty for a long time. The master has meant to help him but doesn’t find a proper chance.” At the thought of this, she looked back for several times, which misled Rian Village to think the girl was attracted by him and felt very excited. He believed that the girl must have a pair of wisdom eye and was his true friend in difficulty.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 02:16, 24 November 2021 (UTC)

The housemaid turned away hurriedly and thought to herself:” the man is so strong, but his clothes are shabby. I don’t have such deprived friends and relatives, thus he must be Jia Yucun that the master has mentioned frequently. It’s said that he will not be trapped in poverty for a long time. The master has always meant to help him but doesn’t find a proper chance.” At the thought of this, she looked back for several times, which misled Yu Cun to think the girl was attracted by him and felt very excited. He believed that the girl must have a good taste and was his true friend in difficulty.--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 11:27, 24 November 2021 (UTC)

==谢佳芬 Xiè Jiāfēn 英语语言文学（英美文学）女 202120081532==

一时小童进来，雨村打听得前面留饭，不可久待，遂从夹道中，自便门出去了。士隐待客既散，知雨村已去，便也不去再邀。一日，到了中秋佳节。

When a child came in, yucun heard that the host entertained the guests meal. Therefore, he knew that he couldn't stay long, so he went out through the lane and went out by himself. Later, Shiyin had already served guests, knowing that yucun had gone, so he didn't invite again. One day, it was the Mid Autumn Festival.

When a child came in, Yucun heard that the host entertained the guests meal. Therefore, he knew that he couldn't stay long, so he went out through the lane and went out by himself. Later, Shiyin had already served guests, knowing that yucun had gone, so he didn't invite again. One day, it was the Mid Autumn Festival.--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:53, 26 November 2021 (UTC)

==谢庆琳 Xiè Qìnglín 俄语语言文学女 202120081533==

士隐家宴已毕，又另具一席于书房，自己步至庙中来邀雨村。原来雨村自那日见了甄家丫鬟曾回顾他两次，自谓是个知己，便时刻放在心上。今又正值中秋，不免对月有怀，因而口占五言一律云：

Shiiyin‘s family banquet has been completed, and another seat in the study, he came to the temple to invite Yucun. It turns out that since that day Yucun saw the Zhen family maid had looked back at him twice, since he said he was a confidant, so he always put on his heart. Now it was the mid-autumn festival, so I couldn't help but feel nostalgic for the moon, so I took five words from the mouth and said.--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:51, 26 November 2021 (UTC)

Shiiyin‘s family banquet has been completed, and another seat in the study, he came to the temple to invite Yucun. It turns out that since that day Yucun saw the Zhen family maid had looked back at him twice, since he said he was a confidant, so he always put on his heart. Now it was the mid-autumn festival, so I couldn't help but feel nostalgic for the moon, so I took five words from the mouth and said.--[[User:Xiong Min|Xiong Min]] ([[User talk:Xiong Min|talk]]) 14:30, 28 November 2021 (UTC)

==熊敏 Xióng Mǐn 英语语言文学（英美文学）女 202120081534==

未卜三生愿，频添一段愁。闷来时敛额，行去几回头。自顾风前影，谁堪月下俦？蟾光如有意，先上玉人楼。

I haven’t realized my dream yet, but had sorrowful experience. I often frown when I feel depressed and look back repeatedly when I farewell. With the wind blowing, I look at my shadow. Who can be my partner? If the moon helps,please shed light on the girl’s window and show her my love.

I haven’t realized my dream yet, but had sorrowful experience. I often frown when I feel depressed and look back repeatedly when I farewell. With the wind blowing, I look at my shadow. Who can be my partner? If the moon helps,please shed light on the girl’s window and show her my love.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 12:02, 28 November 2021 (UTC)

==徐敏赟 Xú Mǐnyūn 语言智能与跨文化传播研究男 202120081535==

雨村吟罢，因又思及平生抱负，苦未逢时，乃又搔首对天长叹，复高吟一联云：玉在椟中求善价，钗于奁内待时飞。恰值士隐走来听见，笑道：“雨村兄真抱负不凡也！”

After Yucun finished reciting the love poems of Jiao Xing, he thought of his great ambitions and thought that he had not met a good time, so he recited a pair of couplets that he created aloud: "Jade and hairpin are all placed in the box, hoping that one day it can realize its value and play its role." Just when Shiyin came to hear it, Shiyin smiled and said, "Brother Yucun is really ambitious!"--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 11:38, 24 November 2021 (UTC)

After Yucun finished reciting the love poems of Jiao Xing, he thought of his great ambitions and thought that he had not met a good time, so he recited aloud a pair of couplets that he created: "Jade and hairpin are all placed in the box, hoping that one day it can realize its value and play its role." Just when Shiyin came to hear it, Shiyin smiled and said, "Yucun is really ambitious!"--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 16:53, 28 November 2021 (UTC)

==颜静 Yán Jìng 语言智能与跨文化传播研究女 202120081536==

雨村忙笑道：“不敢。不过偶吟前人之句，何期过誉如此！”因问：“老先生何兴至此？”士隐笑道：“今夜中秋，俗谓团圆之节。想尊兄旅寄僧房，不无寂寥之感。故特具小酌，邀兄到敝斋一饮。不知可纳芹意否？”

Yucun laughed and hurriedly said, "No no, I just recite the words of the predecessors. You speak too highly of me!" he asked, "Why did you come here, sir?" Shiyin smiled, "Tonight is the reunion time of Mid Autumn Festival. You lodged with a monk's room alone. So I come to invite you to have a drink with me. What do you think?"--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 10:51, 21 November 2021 (UTC)

"Why did you come here, master?"
You are lodged with a monk's room alone. --[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 02:18, 29 December 2021 (UTC)

==颜莉莉 Yán Lìlì 国别女 202120081537==

雨村听了，并不推辞，便笑道：“既蒙谬爱，何敢拂此盛情！”说着，便同士隐复过这边书院中来了。须臾茶毕，早已设下杯盘，那美酒佳肴，自不必说。

Hearing this, Rainvillage Merchant did not refuse, but said with a smile: "Since I am indebted to you, I dare not live up to this feeling." Then he and Hidden Truth came to the academy here. In a moment they had finished their tea, and a feast had already been set up, with wine and food, in which the delicacy was all.

They went to the court in front of Hidden Truth 's study. Soon they had fin rished their tea and sat down to a collation of choice wine and delicacies.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 11:36, 28 November 2021 (UTC)

==颜子涵 Yán Zǐhán 国别女 202120081538==

二人归坐，先是款酌慢饮；渐次谈至兴浓，不觉飞觥献斝起来。当时街坊上家家箫管，户户笙歌；当头一轮明月，飞彩凝辉。二人愈添豪兴，酒到杯干。

At first, they drank slowly,but their spirits rose as they talked and they began to drink more recklessly. At that time, Flutes and strings can be heard everywhere and every family in the neighborhood was singing; When a bright moon rises, The two became more and more cheerful, and the wine dried cup up.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 14:26, 27 November 2021 (UTC)

At first, they drank slowly,but their spirits rose as they talked in depth， they began to drink more recklessly. At that time, the sound of flutes and strings can be heard everywhere and every family in the neighborhood was playing and singing; When a bright moon rises, The two became more and more cheerful and drained cup after cup.--[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 11:39, 28 November 2021 (UTC)

==阳佳颖 Yáng Jiāyǐng 国别女 202120081540==

雨村此时已有七八分酒意，狂兴不禁，乃对月寓怀，口占一绝云：时逢三五便团圆，满把清光护玉栏。天上一轮才捧出，人间万姓仰头看。士隐听了，大叫：“妙极！弟每谓兄必非久居人下者，今所吟之句，飞腾之兆已现，不日可接履于云霄之上了。可贺，可贺！”

WE Rainvillage Merchant, eight-tenths drunk, cannot suppress his high spirits. As he gazed at the moon, he fostered thoughts, to which he gave vent by the recital of a double couplet.

"On the fifteenth the moon is full, Her pure rays fill the court; As her bright orb sails up the sky, All men on earth gaze upwards at the sight."

"Excellent!" cried Hidden Truth with a loud voice, after he had heard these lines; "I have repeatedly maintained that it was impossible for you to remain in a subordinate position for a long period, and now the verses are a prognostic of your rapid advancement. In a few days you will extend your footsteps far above the clouds! Let me congratulate you."！

WE Rainvillage Merchant, eight-tenths drunk, cannot suppress his elation. As he gazed at the moon, he improvised a poetry to the moon and declaimed it:

"On the fifteenth the moon is full, Her pure rays fill the court; As her bright orb sails up the sky, All men on earth gaze upwards at the sight."

"Excellent!" cried Hidden Truth with a loud voice, after he had heard these lines; "I have repeatedly maintained that it was impossible for you to remain in a subordinate position for a long period, and now the verses reveals your rapid advancement. In a few days you will extend your footsteps far above the clouds! Let me congratulate you."！--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 04:36, 28 November 2021 (UTC)

==杨爱江 Yáng Àijiāng 英语语言文学（语言学）女 202120081541==

乃亲斟一斗为贺。雨村饮干，忽叹道：“非晚生酒后狂言，若论时尚之学，晚生也或可去充数挂名。只是如今行李路费，一概无措，神京路远，非赖卖字撰文，即能到得。”士隐不待说完，便道：“兄何不早言？弟已久有此意，但每遇兄时，并未谈及，故未敢唐突。今既如此，弟虽不才，‘义利’二字，却还识得。且喜明岁正当大比，兄宜作速入都，春闱一捷，方不负兄之所学。其盘费馀事，弟自代为处置，亦不枉兄之谬识矣。”

Shiyin filled another large cup of alcohol. Yucun tossed it off and then signed. "Don't think this is just a talk after being drunk," he said, "I'm sure I could acquit myself quite creditably in the examinations, but I have no money in my wallet for my travelling expenses and the capital is far away. I can't raise enough money by selling my words and articles ...." "Why didn't you say so before?" interjected Shiyin. "I've always thought about this, but since you never mentioned it it is inappropriate for me to mention this subject. If that's how things are, dull as I am at least I know what's due to a firend. Luckily the Metropolitan Examinations are coming up next year. You must go as fast as you can to the capital and prove your learning in the Spring Test. I shall take it an honor to take care of the travelling expenses and other business for you."--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 04:28, 28 November 2021 (UTC)

Hidden Truth filled another large cup of alcohol for congratulation. Rainvillage Merchant tossed it off and then sighed: "Don't think this is just a talk after drinking. I'm sure I could acquit myself quite creditably in the examinations, but I have no money in my wallet for my travelling expenses and the capital is far away. I can't raise enough money only by selling my words and articles ...." "Why didn't you say that before?" interjected Hidden Truth. "I've always thought about this, but since you never mentioned it.It is inappropriate for me to mention this subject. If that's how things are, dull as I am at least I know what's due to a real friend. Luckily the Metropolitan Examinations are coming up next year. You must go as fast as you can to the capital and prove your learning in the Spring Test. I shall take it an honor to take care of the travelling expenses and other business for you."--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 11:43, 28 November 2021 (UTC)

==杨堃 Yáng Kūn 法语语言文学女 202120081542==

当下即命小童进去，速封五十两白银并两套冬衣。又云：“十九日乃黄道之期，兄可即买舟西上。待雄飞高举，明冬再晤，岂非大快之事！”雨村收了银、衣，不过略谢一语，并不介意，仍是吃酒谈笑。

Hidden Truth immediately ordered the child to go in and quickly seal fifty liang silver and two sets of winter clothes. And he also said, "the 19th of March is the time of the zodiac, and you can buy a boat to the west. Isn't it a great pleasure to wait for triumph of the war[1] and meet again the next winter?" Rainvillage Merchant received the silver and clothes, but he thanked Hidden Truth a little. He didn't mind and was still drinking wine, talking and laughing.

[1]The war between Li Zicheng and the emperor Chongzhen. On March 19 of the lunar calendar in 1644, Emperor Chongzhen of the Ming Dynasty hanged himself. Then, Li Zicheng entered Beijing to overthrow the Ming Dynasty.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 03:23, 21 November 2021 (UTC)

Shiyin immediately ordered the child in and seal fifty liang silver and two suits of winter clothes quickly. Then he said, "the 19th of March is favorable time, and you can buy a boat to the west. Isn't it a great pleasure to wait for triumph of the war[1] and meet again the next winter?" Yucun received the silver and clothes, but he thanked Shiyin a little. He didn't mind and was still drinking wine, talking and laughing.

[1]The war between Li Zicheng and the emperor Chongzhen. On March 19 of the lunar calendar in 1644, Emperor Chongzhen of the Ming Dynasty hanged himself. Then, Li Zicheng entered Beijing to overthrow the Ming Dynasty.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 12:15, 23 November 2021 (UTC)

==杨柳青 Yáng Liǔqīng 英语语言文学（英美文学）女 202120081543==

那天已交三鼓，二人方散。士隐送雨村去后，回房一觉，直至红日三竿方醒。因思昨夜之事，意欲写荐书两封与雨村，带至都中去，使雨村投谒个仕宦之家，为寄身之地。

Jia Yunchun and Zhen Shiyin drank until midnight and then dispersed. Zhen Shiyin sent Jia Yuchun bedchamber and went back his room to sleep. He didn't wake up until the late morning. Considering Zhen Shiyin's bad conditions, Zhen Shiyin intended to write two recommendation letters for Jia Yuchun, so Jia Yuchun could take and deliver it to a family of dignities in Qi Zhou city to find a place to stay.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 06:10, 25 November 2021 (UTC)

These two friends drank until midnight and then left. Zhen Shiyin sent Jia Yuchun back to his bedchamber and headed back to sleep. He didn't wake up until the noon time. Zhen Shiyin intended to write two recommendation letters for Jia Yuchun considering his bad condition, so Jia Yuchun could take and deliver it to some family of dignities in Qi Zhou city to find a fine place to settle.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 05:11, 29 November 2021 (UTC)

==叶维杰 Yè Wéijié 国别男 202120081544==

因使人过去请时，那家人回来说：“和尚说：贾爷今日五鼓已进京去了，也曾留下话与和尚转达老爷，说：‘读书人不在黄道黑道，总以事理为要，不及面辞了。’”士隐听了，也只得罢了。真是闲处光阴易过，倏忽又是元宵佳节。

The family came back and said, “The monk said: The Five Drums of Master Jia has entered Beijing today, and he also left a message with the monk to convey to the master, saying:'The scholar is not in the zodiacal and underworld, and he always takes affair as the priority. , It's too late to resign.'" Shiyin listened and had no choice but to leave. It's really easy to spend leisure time, and suddenly it is the Lantern Festival.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 13:21, 28 November 2021 (UTC)

When the family came back, they said, "The monk said that Master Merchant had gone to the capital between three and five o'clock today, and had left a message for the monk to convey to you, saying, 'No matter what the background of a scholar is, it is always important to take care of things, so it is too late to say goodbye.'" When Hidden Truth heard this, he had no choice but to do nothing. It was easy to spend time at leisure, and suddenly it was the Lantern Festival again.--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 13:36, 28 November 2021 (UTC)Yi Yangfan

==易扬帆 Yì Yángfān 英语语言文学（英美文学）女 202120081545==

士隐令家人霍启抱了英莲，去看社火花灯。半夜中霍启因要小解，便将英莲放在一家门槛上坐着。待他小解完了来抱时，那有英莲的踪影。

Zhen Shiyin asked his family member Huo Qi to carry Yinglian and go to see the lanterns. In the middle of the night, Huo Qi had to take a piss, so he left Yinglian sitting on the threshold of a door. When he came to carry her after taking a piss, there was no sign of Yinglian.

Hidden Truth asked his family member trouble beginner to carry Pity Zhen and go to see the lanterns. In the middle of the night, trouble beginner left Pity Zhen alone sitting on the threshold of a door because of the urgency of urinating. When he came back, Pity Zhen disappeared.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 09:11, 27 November 2021 (UTC)

==殷慧珍 Yīn Huìzhēn 英语语言文学（英美文学）女 202120081546==

急的霍启直寻了半夜，至天明不见。那霍启也不敢回来见主人，便逃往他乡去了。那士隐夫妇见女儿一夜不归，便知有些不好。再使几人去找寻，回来皆云影响全无。

Huo Qi was so anxious that he looked for her all night and did not find her by dawn. So he did not dare to return to meet the host and he fled to his hometown. Mr. and Mrs. Shi Yin felt something is about to go wrong when they found their daughter didn't go home all night. They sent more people to look for her, but when they came back they said they didn't have any trace of her.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 14:22, 21 November 2021 (UTC)

Being so anxious, Huo Qi looked for her all night but in vain till dawn. Dare not to return to his master, he fled to another place. Mr. and Mrs. Shi Yin felt something wrong when their daughter didn't go home all night. More people were sent to look for her, but only to find no trace of her.--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:11, 22 November 2021 (UTC)

==殷美达 Yīn Měidá 英语语言文学（语言学）女 202120081547==

夫妻二人半世只生此女，一旦失去，何等烦恼，因此昼夜啼哭，几乎不顾性命。看看一月，士隐已先得病，夫人封氏也因思女搆疾，日日请医问卦。不想这日三月十五，葫芦庙中炸供，那和尚不小心，油锅火逸，便烧着窗纸。

The couple, having spent half of their lifetime, couldn't bear the thought of losing their only child. They wept day and night, almost risking their lives. In January, Shi Yin was already sick, and his wife Feng shi also fell ill for missing her daughter excessively and had to see doctors and fortunetellers everyday. Unfortunately, on March 15, when frying tributes in the calabash Temple, the careless monk let the fire escape from the oil boiler, which set the window paper on fire.--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:57, 22 November 2021 (UTC)

The couple, having spent half of their lifetime, couldn't bear the annoyance of losing their only daughter. They wept all days and nights, almost risking their lives. In January, Hidden Truth was already sick, and his wife Feng also got ill for missing her daughter excessively and had to call the doctors and fortunetellers everyday. Unfortunately, on March 15, when frying tributes in the calabash Temple, the careless monk let the fire escape from the oil boiler, which set the window paper on fire.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 12:11, 28 November 2021 (UTC)

==尹媛 Yǐn Yuán 英语语言文学（英美文学）女 202120081548==

此方人家俱用竹篱木壁，也是劫数应当如此，于是接二连三，牵五挂四，将一条街烧得如火焰山一般。彼时虽有军民来救，那火已成了势了，如何救得下，直烧了一夜方熄，也不知烧了多少人家。只可怜甄家在隔壁，早成了一堆瓦砾场了，只有他夫妇并几个家人的性命不曾伤了，急的士隐惟跌足长叹而已。

This family deserves this fate for using bamboos and wood as hedge. One by one, the whole street burnt like the Mountain of Flames. At that time, though the army and people came for rescue, the fire had already been too large to put out. It didn't burn until the morning. It cannot be estimated that how many houses had been destroyed. Poor Hiden Truth's house next door had turned into a pile of rubble, only the couple and the families unhurt, which made Hidden Truth anxious and sigh deeply.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 14:44, 22 November 2021 (UTC)

This family deserved this fate for using bamboos and wood as hedge. One house by one house, the whole street burnt like the Mountain of Flames. At that time, though the army and people came for rescue, the fire had already been too large to put out. It didn't burn until the morning. It cannot be estimated that how many houses had been destroyed. The fire had turned Poor Zhen's house next door into a pile of rubble, only the couple and several families unhurt, which made Zhen Shiyin anxious and sigh deeply.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 10:47, 24 November 2021 (UTC)

==詹若萱 Zhān Ruòxuān 英语语言文学（英美文学）女 202120081549==

与妻子商议，且到田庄上去住。偏值近年水旱不收，贼盗蜂起，官兵剿捕，田庄上又难以安身。只得将田地都折变了，携了妻子与两个丫鬟，投他岳丈家去。

He discussed with his wife, and went to live on the farm. However, in recent years, harvests have been ruined by flood and drought, and thieves and robbers have been rising. It was difficult to settle down on the farm. He had to sell his lands at a discount and took his wife and two maids to seek his father-in-law's help.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 10:42, 24 November 2021 (UTC)
Take counsel with his wife, and come to live at the Grange. Partial value in recent years flood and drought do not harvest, thieves bee, officers and soldiers suppression, the grange and difficult to live. He had to change the land and went to his husband's house with his wife and two maids.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 12:22, 28 November 2021 (UTC)

==张秋怡 Zhāng Qiūyí 亚非语言文学女 202120081550==

他岳丈名唤封肃，本贯大如州人氏，虽是务农，家中却还殷实。今见女婿这等狼狈而来，心中便有些不乐。幸而士隐还有折变田产的银子在身边，拿出来托他随便置买些房地，以为后日衣食之计。

His father-in-law's name was Feng Su. His native place was Such State. Although he was a farmer, his family was well off. Now, seeing her son-in-law come in such a discomfiture, I felt unhappy. Fortunately, there are hidden converted field of silver in the side, took out to entrust him to buy some premises, that the day after the means of food and clothing.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 10:19, 21 November 2021 (UTC)

His father-in-law's name was Feng Su, who was originally from Daru State. Although he was a farmer, his family was well off. Now, seeing his son-in-law come in such a discomfiture, he felt unpleasant inside. Fortunately, there are hidden silver of converted field by his side, so he took it out to entrust him to purchase some premises for buying food and clothing in the future.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 11:40, 28 November 2021 (UTC)

==张扬 Zhāng Yáng 国别男 202120081551==

那封肃便半用半赚的，略与他些薄田破屋。士隐乃读书之人，不惯生理稼穑等事，勉强支持了一二年，越发穷了。封肃见面时，便说些现成话儿；且人前人后，又怨他不会过，只一味好吃懒做。

Feng Su made money while using some of it, and provided small fields and a shabby house with him. Shi Yin was a scholar and was not used to farming and other handworks. He reluctantly struggled for a year or two and became poorer and poorer. When Feng Su met him, he said something ready-made. But behind Shiyin's back, he complained that he couldn't live his life well by just being lazy.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 11:34, 28 November 2021 (UTC)

Feng Su made money while using some of it, and provided small fields and a shabby house with him. Hidden Truth was a scholar and was not used to farming and other handworks. He reluctantly struggled for a year or two and became poorer and poorer. When Feng Su met him, he said something ready-made. But behind Shiyin's back, he complained that he couldn't live his life well by just being lazy.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 12:15, 28 November 2021 (UTC)

==张怡然 Zhāng Yírán 俄语语言文学女 202120081552==

士隐知道了，心中未免悔恨；再兼上年惊唬，急忿怨痛：暮年之人，那禁得贫病交攻，竟渐渐的露出那下世的光景来。可巧这日拄了拐，扎挣到街前散散心时，忽见那边来了一个跛足道人，疯狂落拓，麻鞋鹑衣，口内念着几句言词道：

When Hidden Truth found out about this, he felt remorse in his heart; he was also frightened of the previous year, and he felt angry and resentful: a man in his twilight years, who could not help being attacked by poverty and illness, was gradually revealing the scene of his next life. It happened that when he was on crutches, he went to the street for a walk, and suddenly he saw a crippled Taoist, crazy and untidy, with sackcloth shoes and quails, reciting a few words under his breath.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 02:26, 22 November 2021 (UTC)

When Hidden Truth found out this, he felt remorse in his heart; he was also frightened of the previous year, angry and resentful: a man in his twilight， who could not be able to be attacked by poverty and illness, was gradually revealing the scene of his next life. It happened that when he was on crutches, he went to the street for a walk, and suddenly he saw a crippled Taoist, crazy and untidy, with ragged shoes and clothes，reciting a few words under his breath.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 07:00, 22 November 2021 (UTC)

==钟义菲 Zhōng Yìfēi 英语语言文学（英美文学）女 202120081553==

世人都晓神仙好，惟有功名忘不了。古今将相在何方？荒冢一堆草没了。世人都晓神仙好，只有金银忘不了。终朝只恨聚无多，及到多时眼闭了。

The common people know that immortals are good, but they can't forget their achievements and fame. Where are the generals and prime ministers from ancient times to the present？What we can see are just deserted graves full of grass. The common people know that immortals are good, but they can‘t forget gold and silver. Till the end of life，they would regret their inability to create as much wealth as possible when they are alive and regret they are going to the heaven after they have accumulated plenty of wealth.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 02:42, 21 November 2021 (UTC)

All the common people know that immortals are good, but they can't forget their achievements and ambitions. Where are the great ones of old？They are just deserted graves full of grass. All the common people know that immortals are good, but they can‘t forget gold and silver. They grub for money all their lives until death seals up their eyes.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 07:24, 21 November 2021 (UTC)

==钟雨露 Zhōng Yǔlù 英语语言文学（英美文学）女 202120081554==

世人都晓神仙好，只有姣妻忘不了。君生日日说恩情，君死又随人去了。世人都晓神仙好，只有儿孙忘不了。痴心父母古来多，孝顺子孙谁见了？

All men want to be immortals, but dote on the wives they’ve married. Those who swear to love their husband forever, but remarry as soon as he’s dead. All men want to be immortals, but dote on the sons they’ve gotten. Although infatuated parents are numerous, who ever saw really filial sons or daughters?--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 02:05, 21 November 2021 (UTC)

Everyone in the world knows that the gods are good, but only the pretty wife can't forget. You swear to remember your husband’s kindness, but when your husband die, you go away with others. Everyone knows that the gods are good, but only the children and grandchildren cannot be forgotten. There are many loving parents in the past, but who has seen the filial children?--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 09:04, 22 November 2021 (UTC)

==周玖 Zhōu Jiǔ 英语语言文学（英美文学）女 202120081555==

士隐听了，便迎上来道：“你满口说些什么？只听见些‘好’、‘了’，‘好’、‘了’。”那道人笑道：“你若果听见‘好’、‘了’二字，还算你明白。可知世上万般，好便是了，了便是好：若不了，便不好；若要好，须是了。我这歌儿便叫《好了歌》。
When the hermit heard it, he came up and said, "What are you talking about ?" I just hear 'Hao’ (means good), 'Liao' (means end) 'Hao’, ‘Liao'. The man laughed, "If you hear the words 'Hao' and 'Liao', you understand it. In this world, good is end, and the end is good. If there is no end, there is no good, and vice versa. My song is called ‘The Song of ‘Hao’ and ‘ Liao’. ”--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 08:54, 22 November 2021 (UTC)

Hidden Truth came over after heard this and said: “ What are you talking about? I just hear the words ‘good’ and ‘end’.” That man laughed, “ You heard the words ‘good’ and ‘end’, that means you got a few things going for you. In this world, good is end, and end is good. If there is no end, there is no good, and vice versa. My song is called ''All Dood Things Must End''.”--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 12:19, 22 November 2021 (UTC)

==周俊辉 Zhōu Jùnhuī 法语语言文学女 202120081556==

士隐本是有夙慧的，一闻此言，心中早已悟彻，因笑道：“且住，待我将你这《好了歌》注解出来何如？”道人笑道：“你就请解。”士隐乃说道：陋室空堂，当年笏满床。

So intelligent, Hidden Truth understood the essence of the song entirely in his head as soon as he heard it, and said: “ Wait a minute. How about I explain your song ''All Good Things Must End'' ？” The Taoist priest said, laughing : “ Would you please explain.” Hidden Truth then explain: “ The empty and dilapidated rattraps we see today, were the grand mansions full of beds and boards used by dignitaries at that time.”--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 08:01, 22 November 2021 (UTC)

So intelligent as Hidden Truth is, he understood the essence of the song entirely in his head as soon as once hearing it, and said: “ Wait a minute. How about I explain your song ''All Good Things Must End'' ？” The Taoist priest said, laughing : “ Would you please explain.” Hidden Truth then explain: “ The empty and dilapidated rattraps we see today, were the grand mansions full of boards used by courtiers at that time.”--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:23, 23 November 2021 (UTC)

==周巧 Zhōu Qiǎo 英语语言文学（语言学）女 202120081557==

衰草枯杨，曾为歌舞场。蛛丝儿结满雕梁，绿纱今又在蓬窗上。说甚么脂正浓，粉正香，如何两鬓又成霜？
Humble hovels and abandoned halls where courtiers once paid daily calls；Bleak places where weeds and trees scarcely thrive
were once with a show of peace and prosperity．When cobwebs cover the mansion’s gilded beams，and collage casement with choice muslin gleams．Would you of perfumed elegance recite? Even as you speak, the raven locks turn white．--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:06, 23 November 2021 (UTC)

Withered grass and withered poplar, This used to be a place where people sang and danced. The spider silk is full of carved beams, but the green gauze is on the simple window. The fat is thick and the powder is fragrant, how the temples become the color of frost?--[[User:Zhou Qing|Zhou Qing]] ([[User talk:Zhou Qing|talk]]) 15:20, 25 November 2021 (UTC)

==周清 Zhōu Qīng 法语语言文学女 202120081558==

昨日黄土陇头埋白骨，今宵红绡帐底卧鸳鸯。金满箱，银满箱，转眼乞丐人皆谤。正叹他人命不长，那知自己归来丧。

Yesterday the bones were buried in the loess, and the mandarin ducks(allusions to couples) lie under the red silk tent tonight. Boxes full of gold, boxes full of silver, everyone yelled and insulted beggars in a blink of an eye. I'm sighing that the lives of others are not long, and I know I'm back to be mourned.

Yesterday the bones were buried in the loess, then tonight it is the time for a newly married couple to sleep behind bed curtains with burning red candle lights.Boxes full of gold, boxes full of silver, everyone yelled and insulted beggars in a blink of an eye. I'm sighed that the lives of others are not long, but failed to predict my own future after return from the funeral.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 11:36, 28 November 2021 (UTC)

==周小雪 Zhōu Xiǎoxuě 日语语言文学女 202120081559==

训有方，保不定日后作强梁；择膏粱，谁承望流落在烟花巷。因嫌纱帽小，致使锁枷扛；昨怜破袄寒，今嫌紫蟒长。乱烘烘，你方唱罢我登场，反认他乡是故乡。

Though she was well educated according to her parent's plan, one can become a bandit later. She tried her best to marry into a rich family. However, she ended up in a (red-light)? district beyond everyone's expectation. People who are not satisfied with their positions have to spend the rest of their life in a prison in chains. People who used to be very poor and used worn coats to resist the cold were not satisfied with fancy clothes after they became rich. I come on the stage as soon as you have finished your singing in a chaotic manner. Taking other's hometown as my own. --[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 11:42, 22 November 2021 (UTC)--[[User:Mahzad Heydarian|Mahzad Heydarian]] ([[User talk:Mahzad Heydarian|talk]]) 16:56, 23 November 2021 (UTC)

If properly educated under parents' guidance, one can probabaly become a bandit later. Although trying her best to marry a rich man, she ends up with a driftage in the red-light district beyond everyone's expectation. People's unsatisfication with their positions leads to their miserable life in prison with chains on their bodies. People who used to be very poor and used worn coats to resist the cold were not satisfied with gorgeous clothes any more when they became rich. In noisy disorder, you just finished and I come on the scene.Instead, taking other's hometown as my own.--[[User:Zhu Suzhen|Zhu Suzhen]] ([[User talk:Zhu Suzhen|talk]]) 15:17, 25 November 2021 (UTC)

==朱素珍 Zhū Sùzhēn 英语语言文学（语言学）女 202120081561==

甚荒唐，到头来，都是为他人作嫁衣裳。那疯跛道人听了，拍掌大笑道：“解得切，解得切！”士隐便说一声：“走罢。”

It's so ridiculous. In the end, they made wedding clothes for others. Hearing this, the crazy lame Taoist clapped his hands and laughed, saying "All right, all right !" Then Shiyin said, "let's go."

It's ridiculous. In the end, they make wedding clothes for others. The crazy lame Taoist listened, clapped his hands and laughed and said, "it's right, it's right!" Shiyin said, "let's go."--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 11:43, 21 November 2021 (UTC)

== Headline text ==
==邹岳丽 Zōu Yuèlí 日语语言文学女 202120081562==

将道人肩上的搭裢抢过来背上，竟不回家，同着疯道人飘飘而去。当下哄动街坊，众人当作一件新闻传说。封氏闻知此信，哭个死去活来。

He grabbed the lap on the Taoist's shoulder and carried it on his back. He didn't go home and floated away with the crazy Taoist. At that moment, the neighborhood was stirred up and everyone regarded it as a news legend. When Feng heard this letter, he cried to death.--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 11:34, 21 November 2021 (UTC)

==Nadia 202011080004==

只得与父亲商议，遣人各处访寻，那讨音信。

==Mahzad Heydarian 玛莎 202021080004==

无奈何，只得依靠着他父母度日。

He was so helpless that he had to rely on his parents to survive.

==Mariam toure 2020GBJ002301==

幸而身边还有两个旧日的丫鬟伏侍，主仆三人，日夜作些针线，帮着父亲用度。

==Rouabah Soumaya 202121080001==

那封肃虽然每日抱怨，也无可奈何了。
Although Feng Su complained every day, he was helpless

==Muhammad Numan 202121080002==

这日那甄家的大丫鬟在门前买线，忽听得街上喝道之声。
The other day, the eldest maid of the Chen family was buying thread at the door when she heard a shout from the street.--[[User:Atta Ur Rahman|Atta Ur Rahman]] ([[User talk:Atta Ur Rahman|talk]]) 14:50, 23 November 2021 (UTC)

==Atta Ur Rahman 202121080003==

众人都说：“新太爷到任了。”
Everyone said: "The new grandfather has arrived"

==Muhammad Saqib Mehran 202121080004==

丫鬟隐在门内看时，只见军牢、快手一对一对过去，俄而大轿内抬着一个乌帽猩袍的官府来了。
When the maid concealed in the door, she saw the military jail and quick hands passing one by one, and the official mansion carrying a black hat and ape robe came in the big sedan chair.

==Zohaib Chand 202121080005==

那丫鬟倒发了个怔，自思：“这官儿好面善，倒像在那里见过的。”

<nowiki>Insert non-formatted text here</nowiki>
The maid was startled, and thought to herself: "This official is so good-natured, but it looks like someone I've seen there."

==Jawad Ahmad 202121080006==

于是进入房中，也就丢过，不在心上。

Then she went into the room and laid the matter aside ，without taking it to heart.

==Nizam Uddin 202121080007==

至晚间正待歇息之时，忽听一片声打的门响，许多人乱嚷，说：“本县太爷的差人来传人问话！”

English:
When I was about to rest in the evening, I heard a bang on the door suddenly, and many people shouted in disorder, saying, "The county's grandfather's messenger is here for questioning!"

==Öncü 202121080008==

封肃听了，唬得目瞪口呆。

Fengsu hear it,he gaped in consternation --[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 13:28, 22 November 2021 (UTC)

==Akira Jantarat 202121080009==

不知有何祸事，且听下回分解。

Don't know something calamity happened, will describe in the ensuing chapter.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 06:36, 21 November 2021 (UTC)

If you don't know what calamity took place, listen to the break down given in the next chapter.--[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 12:54, 21 November 2021 (UTC)

==Benjamin Wellsand 202111080118==

通灵──“通灵宝玉”的简称。Psychic--short for ''Psychic Treasure.--[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 12:48, 21 November 2021 (UTC)

Psychic -- the abbreviation for "Psychic Treasure". --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 03:35, 24 November 2021 (UTC)

==Asep Budiman 202111080020==

亦即下文所说女娲炼石补天所剩的那块“顽石”，因其历经锻炼而“灵性已通”，并能幻化为贾宝玉，故称。

That is to say, the "stubborn stone" left by Nüwa's refining stone to replenish the sky. As it has undergone training, it has "spiritual achievement" and can be transformed into Jia Baoyu, so it is called. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 03:48, 24 November 2021 (UTC)

That is to say, the "stubborn stone" left by Nüwa's refining stone to replenish the sky, because it has undergone training, has "spiritually achieved" and can be transformed into Jia Baoyu, so it is called.--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 06:10, 24 November 2021 (UTC)Ei Mon Kyaw

==Ei Mon Kyaw 202111080021==

《石头记》──此书的本名。
"Story of the Stone" - the original name of the book. --[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 06:26, 24 November 2021 (UTC)Ei Mon Kyaw

20211124 homework

2021-12-29T08:53:00Z

Wei Yiwen: /* 卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526 */

Quicklinks: [[Introduction_to_Translation_Studies_2021|Back to course homepage]] [https://bou.de/u/wiki/uvu:Community_Portal#Frequently_asked_questions_FAQ FAQ] [https://bou.de/u/wiki/uvu:Community_Portal Manual] [[20210926_homework|Back to all homework webpages overview]] [[20220112_final_exam|final exam page]]

==陈静 Chén Jìng 国别女 202020080595==

我很纳闷：《不自弃文》是篇名，《姬子》是书名，应该同等对待，要么都予注释，要么都不注释，为什么一注一不注呢？难道前者生僻而需要注释，后者人所共知而不必注释吗？显然不是，只能说是避难就易，这与注释的宗旨完全背道而驰。
I wonder that since No Self-surrender is the title of the passage and Jizi is the title of the book, which should be treated equally, why did the situation happened that one annotated while one did not? Did the former need to be annotated while the latter is known to all without having to be annotated? Obviously, it is for choosing the easier way, which is completely contrary to the purpose of the annotation.

I wonder: "don't abandon yourself" is the title, and "Ji Zi" is the title of the book. It should be treated equally, either annotated or not annotated. Why not annotate one note at a time? Is it true that the former is remote and needs annotation, while the latter is well known and does not need annotation? Obviously not, it can only be said that it is easy to avoid difficulties, which is completely contrary to the purpose of the notes.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 07:01, 24 November 2021 (UTC)

==蔡珠凤 Cài Zhūfèng 法语语言文学女 202120081477==

那怕注为“《姬子》不详”，也还不失为态度诚实。老实说，起初我对《姬子》也一头雾水，因为见所未见，闻所未闻。但根据我自定的注释原则，我不能回避。

Even if it is noted as "Ji Zi" unknown ", it can be regarded as an honest attitude. To be honest, at first I was confused about Ji Zi, because I had never seen or heard of it. But according to my own annotation principle, I can't avoid it.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 11:20, 21 November 2021 (UTC)

Even if it is noted as "unknown Ji Zi" , it can still be regarded as an honest attitude. To be honest, at first I was confused about ''Ji Zi'', because I had never seen or heard of it. But according to my own annotation principle, I can't avoid it.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 14:36, 22 November 2021 (UTC)Chen Huini

==陈惠妮 Chén Huìnī 英语语言文学（英美文学）女 202120081479==

于是我首先求助于《中国古典数字工程》，肯定了中国根本不存在《姬子》这么一本书，完全是曹雪芹所杜撰，正如《古今人物通考》、《中国历代文选》都是曹雪芹杜撰一样。其次，我记得俞平伯先生有一篇专门解释《姬子》的文章，但文章的题目、发表时间以及文章内容却不记得了。经过两天的翻箱倒柜，我终于找到了这篇文章，它的题目是《读〈红楼梦〉随笔》第九节《姬子》，初载于《文汇报》1954年1月25日；又收入《红楼梦研究参考资料选辑》第二辑，人民文学出版社1973年11月出版。

Therefore, I first made reference htiw "Chinese Classical Digital Engineering" and confirmed that there was no such a book called "Ji Zi" in China, which was completely written by Cao Xueqin, just as Cao Xueqin wrote "General Examination of Ancient and Modern Characters" and "Selected Chinese Writings in Past Dynasties". Secondly, I remember that Mr. Yu Pingbo had a special article explaining ''JiZi'', but I do not remember the title, publication time and content of the article. After two days of searching, I finally found this article. Its title is ''Ji Zi'', section 9 of Essays on Reading ''A Dream of Red Mansion''. It was first published in Wenhui Daily on January 25, 1954. It was also included in the second series of ''Selected Research Reference Materials on A Dream of Red Mansion'', published by People's Literature Publishing House in November 1973.--[[User:Chen Huini|Chen Huini]] ([[User talk:Chen Huini|talk]]) 14:46, 22 November 2021 (UTC)Chen Huini

So, I firstly searched ''Chinese Classical Digital Engineering'' and confirmed there was no such a book called "Ji Zi" in China. This book was completely made up by Cao Xueqin like the same thing he did to ''General Examination of Ancient and Modern Characters'' and ''Selected Chinese Writings in Past Dynasties''.Then, I recalled that Mr. Yu Pingbo especially wrote an article to explain ''Ji Zi'', but I didn't remember the title, publication time and content.After two days of searching, I finally found it. The title of it was ''Ji Zi'', section 9 of Essays on Reading ''A Dream of Red Mansion'' which was first published in Wenhui Daily on January 25, 1954. and then was included in the second series of ''Selected Research Reference Materials on A Dream of Red Mansion'', published by People's Literature Publishing House in November 1973.--[[User:Chen Xiangqiong|Chen Xiangqiong]] ([[User talk:Chen Xiangqiong|talk]]) 00:20, 24 November 2021 (UTC)

==陈湘琼 Chén Xiāngqióng 外国语言学及应用语言学女 202120081480==

据俞先生在文章中说：姬子书到底是部什么书呢，谁也说不上来。特别前些日子把这一回书选为高中国文的教材，教员讲解时碰到问题，每来信相询，我亦不能对。但经过研究，他还是写了这篇文章，作为回答。

According to Mr.Yu in his article: nobody can tell what book ''Ji Zi'' really is. Moreover, this chapter of ''A Dream in Red Mansions'' with the name ''Ji Zhi'' has been selected as the reading material of the high school,and I can't say anything when the teacher who failed to explain it in the classroom come to me.But after careful research, he still write an article to reply this question.

According to Mr. Yu in his article: nobody can tell what book ''Ji Zi'' really is. In particular, this chapter was selected as a reading material for the Chinese language in high school some days ago, the teachers encountered problems when explaining it, and they wrote to me every time to ask about it, but I couldn't get it right. But after researching, he wrote this article as an answer.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:37, 23 November 2021 (UTC)

==陈心怡 Chén Xīnyí 翻译学女 202120081481==

他的结论有三点：其一，《姬子》是“作者杜撰”，并以第三回的《古今人物通考》也是杜撰而作为佐证。其二，“这原来是一个笑话”，是探春“拿姬子来抵制”宝钗用以压人的朱子和孔子，而“比朱子孔子再大，只好是姬子了。殆以周公姓姬，作为顽笑”。

There are three points in his conclusion: one, ''Ji Zi'' is "the author fabricated", and to the third round of " the general examination of ancient and modern characters" is also fabricated and as proof. Second, "this turns out to be a joke", is Tanchun " take ''Ji Zi'' to resist" Baochai and used to press people by citing Zhu Zi and Confucius, and "higher level than Zhu Zi and Confucius can only be ''Ji Zi''. Probably Zhou Gong was surnamed Ji as a joke.--[[User:Chen Xinyi|Chen Xinyi]] ([[User talk:Chen Xinyi|talk]]) 05:35, 23 November 2021 (UTC)
There are three points in his conclusion: first, ''Ji Zi'' is "fabricated by the author", and can be proved by the fabrication of the third round of " the general examination of ancient and modern characters". Second, "this turns out to be a joke", which Tanchun " held ''Ji Zi'' to resist” Baochai who used to press her by citing Zhu Zi and Confucius, but “requiring higher level than Zhu Zi and Confucius, there’s only be ''Ji Zi''. Probably Zhou Gong was surnamed Ji as a joke.”--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 12:25, 23 November 2021 (UTC)

==程杨 Chéng Yáng 英语语言文学（英美文学）女 202120081482==

其三，“有人或者要问为什么净瞎捣乱，造书名？我回答：这是小说。”《中国古典数字工程》可以证明俞先生的“杜撰说”是正确的，因此我把俞先生的意见用以注释《姬子》。
Thirdly, "Someone may ask why messing around and making a title? I replied: This is a novel. "It can be proved by ''The Chinese Classical Digital Engineering'' that Mr. Yu’s “theory of fabrication” is correct. Therefore, I applied Mr. Gong's opinion to annotate ''Jizi''.--[[User:Cheng Yang|Cheng Yang]] ([[User talk:Cheng Yang|talk]]) 04:56, 23 November 2021 (UTC)

Thirdly, "Someone may ask why to mess around and make a title? I replied: This is a novel. "It can be proved by ''The Chinese Classical Digital Engineering'' that Mr. Yu’s ''Theory of Fabrication'' is correct. Therefore, I applied Mr. Gong's opinion to annotate ''Ji Tzu''.--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 11:01, 26 November 2021 (UTC)

==丁旋 Dīng Xuán 英语语言文学（英美文学）女 202120081483==

据我所知，现在有人搜集了周公的几篇佚文，将其编为集子，按照《老子》、《庄子》、《孟子》之类的惯例，即命名为《姬子》，但这与曹雪芹毫不相干，《红楼梦》中的《姬子》书名绝对是杜撰。此外，有的注本虽然对《不自弃文》作了注释，却只是简述该文的大意，而没有注出曹雪芹的深刻用意。原来朱熹的徒子徒孙认为此文格调低下，有失朱夫子的身份，故将此文排除在众多朱熹文集之外，只有明·朱培编《文公大全集补遗》卷八从抄本《朱熹家谱》中引录，另有《朱子文集大全类编·卷二一·庭训》亦予收录。

As far as I know, someone collected several lost articles of Duke of Zhou, edited them into an anthology and named it ''Ji Tzu'' according to the routine of ''Lao Tzu'', ''Chang Tzu'' and ''Mencius'' and so on. However, this thing is irrelevant to Cao Xueqin, so the title of ''Ji Tzu'' in ''A Dream in Red Mansions'' is absolutely fabricated. Besides, although some books with annotations made interpretation to ''No Self-surrender'', they just told the main idea of this article rather than annotating the deep meaning made by Cao Xueqin. In fact, disciples and followers of Zhu Xi thought the style of this passage beneath his dignity is very low, so they excluded it out of many anthologies of Zhu Xi. Only when Zhu Pei(Ming dynasty) edited the eighth roll of ''Supplement to Collected Works of Duke Wen'', he incited it from transcript of ''Zhu Xi’s Genealogy''. In addition, it is also included in ''Complete Works of Zhu Tzua•Roll Twenty-one•Home Hearing''.--[[User:Ding Xuan|Ding Xuan]] ([[User talk:Ding Xuan|talk]]) 03:47, 21 November 2021 (UTC)

As far as I know, now someone collected several lost articles of Duke of Zhou and edited them into a collection that was named ''Ji Tzu'' according to the routine of ''Lao Tzu'', ''Chang Tzu'' and ''Mencius'' and so on. However, this thing is irrelevant to Cao Xueqin, so the title of ''Ji Tzu'' in ''A Dream in Red Mansions'' is absolutely fabricated. Besides, although some books with annotations made interpretations to ''No Self-surrender'', they just briefly described the main idea of this article rather than annotating the deep meaning of Cao Xueqin. In fact, disciples and followers of Zhu Xi thought this passage was low in style and demeaned Zhu Xi, so they excluded it out of many anthologies of Zhu Xi. Only when Zhu Pei(Ming dynasty) edited the Book Eight of ''Supplement to Collected Works of Duke Wen'', he incited it from transcript of Zhu Xi’s Genealogy. In addition, ''Complete Works of Zhu Tzua• Book Twenty-one•Home Hearing'' was also included.--[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 03:07, 22 November 2021 (UTC)

==杜莉娜 Dù Lìna 英语语言文学（语言学）女 202120081484==

曹雪芹借宝钗之口说出这篇少见的文章，一则以显示宝钗无书不读，再者也暗示自己博览群籍，同时也对那些自封的朱熹卫士予以调侃。可见曹雪芹即使开玩笑，也非闲笔，总有一定的用意。（详见注释）鉴于所要注释的词语性质不同，因此对注文的要求也有所不同。

Saying this rare writing through Precious Hairpin Marshgrass, on the one hand Cao Xueqin showed her strong love of reading as well as implied own extensive reading, and on the other, he played off those self-appointed guards of Zhu Xi. Obviously, his joking is not casual but absolutely with some profound meaning.(see annotations) The nature of words annotated is different, so the requirements for explanatory notes are different as well.--[[User:Du Lina|Du Lina]] ([[User talk:Du Lina|talk]]) 02:41, 22 November 2021 (UTC)

==付红岩 Fù Hóngyán 英语语言文学（英美文学）女 202120081485==

其一，对于一般的疑难词语，重在疏通文意，多不引经据典，追根溯源。其二，对于成语、典故，则既要注明其出典，又要解释其本义，还要说明其引申义或比喻义。其三，对于各种名物（如建筑、服饰、官署、官职、琴棋书画、医卜星相等），则力求变专门术语为通俗语言，以利读者理解。

Firstly, as for normally confusing words, the emphasis is on clearing up the meaning of the text, as much quoting scripture and tracing the roots as possible. Secondly, for idioms and allusions, it is necessary to indicate their origins, explain their original meanings, and also include their derivative meanings or metaphorical meanings. Thirdly, for all kinds of physical objects (such as architecture, costumes, official offices, official positions, Four Arts( qin, chess, calligraphy and painting), medicine, divination and astrology, etc.), the attempt is to turn specialized terms into common language in order to facilitate readers’ understanding.--[[User:Fu Hongyan|Fu Hongyan]] ([[User talk:Fu Hongyan|talk]]) 11:24, 24 November 2021 (UTC)

Firstly, as for common confusing words, it should emphasize on clearing up the meaning of the text, as much quoting scripture and tracing the roots as possible. Secondly, for idioms and allusions, it is necessary to indicate their origins, explain their original meanings, and also include their derivative meanings or metaphorical meanings. Thirdly, for various technical terms of objects (such as architecture, costumes, official offices, official positions, Four Arts( qin, chess, calligraphy and painting), medicine, divination and astrology, etc.), the attempt is to turn specialized terms into common language in order to facilitate readers’ understanding.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 12:17, 28 November 2021 (UTC)

==付诗雨 Fù Shīyǔ 日语语言文学女 202120081486==

其四，对于历史名人，则注明其所在朝代、简历及突出事迹。对于传说人物，则注明其出处及相关故事。其五，对于珍禽异兽、奇花异卉等，则注明其出处来历、奇异之处及相关故事。

Fourthly, as for historical celebrities, their dynasties, resumes and outstanding deeds should be indicated. As for legendary figures, their sources and related stories should be indicated. Fifthly, as for rare birds and animals, unusual flowers and different plants, etc., their origins and histories, peculiar places and related stories should be indicated.--[[User:Fu Shiyu|Fu Shiyu]] ([[User talk:Fu Shiyu|talk]]) 14:36, 23 November 2021 (UTC)

Fourthly, as for historical celebrities, their dynasties, resumes and outstanding deeds should be indicated. As for legendary figures, their sources and related stories should be indicated. Fifthly, as for rare birds and fabulous beasts, unusual flowers and different plants, etc., their origins and histories, peculiarities and related stories should be indicated.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 15:50, 23 November 2021 (UTC)

==高蜜 Gāo Mì 翻译学女 202120081487==

其六，对于风俗、礼仪、节气等，则注明其形成沿革、具体内容。其七，对于谜语，则既要揭出谜底，又要解释谜语中的疑难词语、成语典故，还要说明谜底的根据。对于酒令，则要参照令谱，详述酒令的玩法及过程。

Sixthly, in terms of customs, etiquette and solar terms, its formation, development and content should be indicated. Seventhly, in terms of riddles, answers should be uncovered and an explanation is expected to be given to the answer as well as to difficult words, idioms and allusions in the riddle. Finally, in terms of drinking games, elaboration should be given on the rules and the process according to the instruction manual.--[[User:Gao Mi|Gao Mi]] ([[User talk:Gao Mi|talk]]) 15:51, 23 November 2021 (UTC)

Sixthly, in terms of customs, etiquette and solar terms, its formation, development and content should be indicated. Seventhly, in terms of riddles, answers should be uncovered and it is necessary to explain the difficult words and idioms in the riddle, and to explain the basis of the answer.Finally, in terms of drinking games, elaboration should be given on the rules and the process according to the instruction manual.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 05:45, 27 November 2021 (UTC)

==宫博雅 Gōng Bóyǎ 俄语语言文学女 202120081488==

其八，对于所引前人诗、词、曲、文等，皆要注明出处；诗、词、曲照录全文，文则节录相关的文字。其九，对于具有隐寓或暗示意味的诗、词、曲、文、成语、典故、谜语、酒令等，因其关系到故事情节的发展和人物性格、运命的描写，故除了作注释之外，还要揭示其隐藏的含义。总而言之，注文以释难为易、释疑为明为宗旨，以释义准确、释文简炼为目标。

Eighthly, reference to predecessors' poems, Ci, Qu, essay, etc., must indicate the source; Poems, Ci, Qu are transcribed without changing the original words, and the essay takes the relevant words. Ninthly, for poems, Ci, Qu, essay, idioms, allusions, riddles, drinkers’ wager game and so on with implicit or suggestive meaning, because they are related to the development of the story plot and the description of the character and fate, so in addition to making annotations, but also to reveal his hidden meaning. In a word, the annotations aim to explain the difficulty as easy, to explain the doubt as clear. Aim to explain the meaning accurately and explain the text concisely.--[[User:Gong Boya|Gong Boya]] ([[User talk:Gong Boya|talk]]) 05:32, 27 November 2021 (UTC)

Eight, all quotations from poems, lyrics, songs and essays should be attributed to the source; the poems, lyrics and songs should be reproduced in their entirety, while the essays should be excerpted from the relevant texts. Nine, for poems, lyrics, songs, texts, idioms, allusions, riddles, wine orders, etc., which have an implicit or suggestive meaning, as they relate to the development of the storyline and the description of the characters' personalities and fortunes. The commentary should reveal their hidden meanings in addition to annotations. All in all, the aim of the commentary is to explain the difficult for the easy and the doubtful for the clear, and to explain the meaning accurately and to explain the text concisely.--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 12:32, 28 November 2021 (UTC)

==何芩 Hé Qín 翻译学女 202120081489==

愿望虽然如此，但学力有限，经验欠缺，愿望能否实现，毫无把握。诚望方家指教，读者检验。

第一回甄士隐梦幻识通灵贾雨村风尘怀闺秀

Although I wish to do so, I am not sure whether my wish can be realized because of my limited learning and lack of experience.I hope that the readers will test it.

Chapter 1 Hidden Turth--[[User:He Qin|He Qin]] ([[User talk:He Qin|talk]]) 12:33, 28 November 2021 (UTC)

Although I wish to do so, I am not sure whether the wish can come true with my limited ability and experience. Sincerely hope that other authors teach something and readers check it.

Chapter 1 Zhen Shiyin, in a vision, apprehends spirituality. Jia Yucun, in the windy and dusty world, cherishes fond thoughts of a beautiful maiden. --[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 07:21, 24 November 2021 (UTC)

==胡舒情 Hú Shūqíng 英语语言文学（语言学）女 202120081490==

此开卷第一回也。作者自云：曾历过一番梦幻之后，故将真事隐去，而借“通灵”之说，撰此《石头记》一书也，故曰“甄士隐”云云。但书中所记何事何人

This is the first chapter of the book. The author said that after going through the illusion, he prefered covering some truth and in virtue of mysticism wrote the novel ''The Story of the Stone''，so instead he used the name of Zhen Shiyin as a major speaker. But things and people noted in it--[[User:Hu Shuqing|Hu Shuqing]] ([[User talk:Hu Shuqing|talk]]) 03:59, 23 November 2021 (UTC)

This is the first chapter of the book.Subsequent to the visions of a dream which he had，on some previous occasion，experienced，the writer personally relates，he designedly concealed the true circumstances，and borrowed the attributes of perception and spirituality to relate this story of the Record of the Stone. With this purpose，he made use of such designations as Chen Shih-yin and the like. What are，however，the events recorded in this work？--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 10:19, 24 November 2021 (UTC)

==黄锦云 Huáng Jǐnyún 英语语言文学（语言学）女 202120081491==

自己又云：“今风尘碌碌，一事无成。忽念及当日所有之女子，一一细考较去，觉其行止见识，皆出我之上；我堂堂须眉，诚不若彼裙钗：我实愧则有馀，悔又无益，大无可如何之日也。当此日，欲将已往所赖天恩祖德，锦衣纨袴之时，饫甘餍肥之日，背父兄教育之恩，负师友规训之德，以致今日一技无成、半生潦倒之罪，编述一集，以告天下：知我之负罪固多，然闺阁中历历有人，万不可因我之不肖，自护己短，一并使其泯灭也。

The author speaking for himself, goes on to explain, with the lack of success which attended every single concern, I suddenly bethought myself of the womankind of past ages. Passing one by one under a minute scrutiny, I felt that in action and in lore, one and all were far above me; that in spite of the majesty of my manliness, I could not, in point of fact, compare with these characters of the gentle sex. And my shame forsooth then knew no bounds; while regret, on the other hand, was of no avail, as there was not even a remote possibility of a day of remedy.On this very day it was that I became desirous to compile, in a connected form, for publication throughout the world, with a view to (universal) information, how that I bear inexorable and manifold retribution; inasmuch as what time, by the sustenance of the benevolence of Heaven, and the virtue of my ancestors, my apparel was rich and fine, and as what days my fare was savory and sumptuous, I disregarded the bounty of education and nurture of father and mother, and paid no heed to the virtue of precept and injunction of teachers and friends, with the result that I incurred the punishment, of failure recently in the least trifle, and the reckless waste of half my lifetime. There have been meanwhile, generation after generation, those in the inner chambers, the whole mass of whom could not, on any account, be, through my influence, allowed to fall into extinction, in order that I, unfilial as I have been, may have the means to screen my own shortcomings.--[[User:Huang Jinyun|Huang Jinyun]] ([[User talk:Huang Jinyun|talk]]) 12:42, 22 November 2021 (UTC)

The author goes on to explain, with the lack of success which attended every single concern, I suddenly bethought myself of the womankind of past ages. Thinking of them one by one under a minute scrutiny, I felt that in action and in lore, one and all were far above me; that in spite of the majesty of my manliness, I could not, in point of fact, compare with these characters of the gentle sex. And my shame forsooth then knew no bounds; while regret, on the other hand, was of no avail, as there was not even a remote possibility of a day of remedy.On this very day it was that I became desirous to compile, in a connected form, for publication throughout the world, with a view to (universal) information, how that I bear inexorable and manifold retribution; inasmuch as what time, by the sustenance of the benevolence of Heaven, and the virtue of my ancestors, my apparel was rich and fine, and as what days my fare was savory and sumptuous, I disregarded the bounty of education and nurture of father and mother, and paid no heed to the virtue of precept and injunction of teachers and friends, with the result that I incurred the punishment, of failure recently in the least trifle, and the reckless waste of half my lifetime. There had been meanwhile, generation after generation, those in the inner chambers, the whole mass of whom could not, on any account, be, through my influence, allowed to fall into extinction, in order that I, unfilial as I have been, may have the means to hide my own shortcomings.--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 14:34, 22 November 2021 (UTC)

==黄逸妍 Huáng Yìyán 外国语言学及应用语言学女 202120081492==

所以蓬牖茅椽，绳床瓦灶，并不足妨我襟怀；况那晨风夕月，阶柳庭花，更觉得润人笔墨。我虽不学无文，又何妨用假语村言敷演出来，亦可使闺阁昭传，复可破一时之闷，醒同人之目，不亦宜乎？”故曰“贾雨村”云云。

"Though my home is now a thatched cottage in which there are shabby windows, bed made of rope and earthen stove, all of these can not change my being broad and level. Besides, the morning breeze, the dew of night, the willows by me steps and the flowers in the yard inspired me to wield my pen. Though I have little learning and literary talent, it doesn't matter if I tell a tale in rustic language to record those lovely girls. This should help readers distract them from their worries. And that's the reason why I use the name Rainvillage Merchant."--[[User:Huang Yiyan1|Huang Yiyan1]] ([[User talk:Huang Yiyan1|talk]]) 13:27, 21 November 2021 (UTC)

"Though my home is now a thatched cottage in which there are shabby windows, bed made of rope and earthen stove, all of these can not change my being broad and level. Besides, the morning breeze, the dew of night, the willows by me steps and the flowers in the yard inspired me to wield my pen. Though I have little learning and literary talent, it doesn't matter if I tell a tale in rustic language to record those lovely girls. This should help readers distract them from their worries. And that's the reason why I use the name Jia Yucun."--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 14:19, 23 November 2021 (UTC)

==曾俊霖 Zēng Jùnlín 国别男 202120081478==

更于篇中间用“梦”、“幻”等字，却是此书本旨，兼寓提醒阅者之意。看官：你道此书从何而起？说来虽近荒唐，细玩颇有趣味。

In the middle of the article, the words "dream" and "fantasy" are the purpose of the book and the meaning of reminding readers. Reader: where did you start this book? Although it's absurd, it's fun to play.--[[User:Zeng Junlin|Zeng Junlin]] ([[User talk:Zeng Junlin|talk]]) 13:21, 23 November 2021 (UTC)
In the middle of the article, the words "dream" and "fantasy" are the purpose of the book and the meaning of reminding readers. Reader: where did you start this book? Although it's absurd, it's fun to play.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:33, 24 November 2021 (UTC)Huang Zhuliang

==黄柱梁 Huáng Zhùliáng 国别男 202120081493==

却说那女娲氏炼石补天之时，于大荒山无稽崖，炼成高十二丈、见方二十四丈大的顽石三万六千五百零一块，那娲皇只用了三万六千五百块，单单剩下一块未用，弃在青埂峰下。谁知此石自经锻炼之后，灵性已通，自去自来，可大可小。因见众石俱得补天，独自己无才，不得入选，遂自怨自愧，日夜悲哀。一日，正当嗟悼之际，俄见一僧一道远远而来，生得骨格不凡，丰神迥异，来到这青埂峰下，席地坐谈。It is said that, once upon a time, when Nuwa was refining stones to mend the sky, she refined them into 36,501 pieces of hard stones 12-feet high and 24-feet square on the Wuji Cliff of the Da Huangshan Mountain. Numa, the creator of human beings in Chinese myth, only used 36,500 pieces, leaving only one unused and abandoned it under the Qinggeng Peak.Who knows, after the stone has been refined and created, its spirit has been passed. It can be big or small.Seeing that all the stones were able to mend the sky, he had no talent and could not be selected, so he complained and felt ashamed and mourned day and night. One day, at the time of mourning, he suddenly saw a monk and a Taoism priest with extraordinary personality coming from afar. They came to the Qinggeng Peak and sat on the ground to talk.--[[User:Huang Zhuliang|Huang Zhuliang]] ([[User talk:Huang Zhuliang|talk]]) 13:34, 24 November 2021 (UTC)Huang Zhuliang

It is said that, once upon a time, when Nuwa(Goddesses of Sky-patching) was refining stones to mend the sky, she refined them into 36,501 pieces of hard stones 12-feet high and 24-feet square on the Wuji Cliff of the Da Huangshan Mountain. Numa, the creator of human beings in Chinese myth, only used 36,500 pieces, leaving only one unused and abandoned it under the Qinggeng Peak.Who knows, after the stone has been refined and created, it had its spirit, it moved freely and could be big or small.Seeing that all the stones were able to mend the sky, he had no talent and could not be selected, so he complained and felt ashamed and mourned day and night. One day, at the time of mourning, he suddenly saw a monk and a Taoism priest with extraordinary personality coming from afar. They came to the Qinggeng Peak and sat on the ground to talk.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 05:57, 26 November 2021 (UTC)

==金晓童 Jīn Xiǎotóng 202120081494==

见着这块鲜莹明洁的石头，且又缩成扇坠一般，甚属可爱。那僧托于掌上，笑道：“形体倒也是个灵物了，只是没有实在的好处。须得再镌上几个字，使人人见了，便知你是件奇物。

It was lovely to see this bright and clean stone shrinking like a fan. Resting on his palm, the monk smiled and said, "The body is a spiritual being, but it has no real benefit. Words had to be engraved so that everyone could see you and know that you were a wonder.--[[User:Jin Xiaotong|Jin Xiaotong]] ([[User talk:Jin Xiaotong|talk]]) 15:01, 20 November 2021 (UTC)
Looking at this bright and clean stone shrinking like a fan, which is so lovely, with the stone on his palm the monk smiled and said, "Your body is a spiritual being, but ihas no real benefits. Words should be engraved so that everyone could see you and know that you are a wonder.--[[User:Kuang Yanli|Kuang Yanli]] ([[User talk:Kuang Yanli|talk]]) 11:42, 24 November 2021 (UTC)

==邝艳丽 Kuàng Yànl 英语语言文学（语言学）女 202120081495==

然后携你到那昌明隆盛之邦、诗礼簪缨之族、花柳繁华地、温柔富贵乡那里去走一遭。”石头听了大喜，因问：“不知可镌何字？携到何方？望乞明示。”那僧笑道：“你且莫问，日后自然明白。”
Then take you there, a city-state of prosperity, a family of scholar, a place of flowers and willows. After listening, Stone asked rejoicingly: “I do not know what word I can write? Where I will be taken to? I hope get your instruction.” The monk smiled, “You do not rush into answer, and you will know it some day.”--[[User:Kuang Yanli|Kuang Yanli]] ([[User talk:Kuang Yanli|talk]]) 11:24, 24 November 2021 (UTC)

Then I'll take you for a walk to the prosperous country, the family of poems, gifts and tassels, the prosperous place of flowers and willows, and the gentle and rich township. " The stone was overjoyed when he asked, "I don't know what word to engrave? Where to carry it? I hope to beg clearly." the monk smiled and said, “You do not rush into answer, and you will know it some day.”--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 14:54, 28 November 2021 (UTC)

==李爱璇 Lǐ Àixuán 英语语言文学（语言学）女 202120081496==

说毕，便袖了，同那道人飘然而去，竟不知投向何方。又不知过了几世几劫，因有个空空道人访道求仙，从这大荒山无稽崖青埂峰下经过，忽见一块大石，上面字迹分明，编述历历。空空道人乃从头一看，原来是无才补天，幻形入世，被那茫茫大士、渺渺真人携入红尘、引登彼岸的一块顽石：上面叙着堕落之乡、投胎之处，以及家庭琐事、闺阁闲情、诗词谜语，倒还全备。

Having concluded these words, he put the stone in his sleeve, and proceeded on his journey, in company with the Taoist priest. No one knows where he took the stone. Nor can it be known how many centuries and ages elapsed, before a Taoist priest, named K'ung K'ung, passed, during his researches after the eternal reason and his quest after immortality, by these Ta Huang Hills, Wu Ch'i cave and Ch'ing Keng Peak. Suddenly seeing a large stone, on the surface of which the handwriting on it is clear and the calendar is compiled, K'ung K'ung examined them from first to last. They, in fact, explained how that this stone had originally been devoid of the properties essential for the repairs to the heavens, how it would be transmuted into human form and introduced by Mang Mang the High Lord, and Miao Miao, the Divine, into the world of mortals, and how it would be led over the other bank (across the San Sara). On the surface, it describes the land of degeneration, the place of reincarnation, as well as family trivia, boudoir leisure, poetry, riddles, which could not be ascertained.--[[User:Li Aixuan|Li Aixuan]] ([[User talk:Li Aixuan|talk]]) 04:54, 24 November 2021 (UTC)

Having concluded these words, he put the stone in his sleeve, and proceeded leisurely on his journey, in company with the Taoist priest. However, no one knew where he went. Nor can it be known how many centuries and ages elapsed, before a Taoist priest, K'ung K'ung by name, passed, during his researches after the eternal reason and his quest after immortality, by these Da Huang Hills, Wu Ch'i cave and Ch'ing Keng Peak. Suddenly perceiving a large block of stone, on the surface of which the traces of characters giving in a connected form, the various incidents of its fate could be clearly predicted. K'ung K'ung examined them from beginning to end. In fact, they explained how this block of worthless stone which had originally been devoid of the properties essential for the mending to the heavens, would be transmuted into human form and introduced by Mang Mang the High Lord, and Miao Miao, the Divine, into the world of mortals, and how it would be led over the other world (across the San Sara). On the surface, it recorded the spot of its degeneration and the place of its birth. The complete recording also included various family trifles, trivial affairs of young ladies, verses and riddles.--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 06:17, 28 November 2021 (UTC)

==李瑞洋 Lǐ Ruìyáng 英语语言文学（英美文学）女 202120081497==

只是朝代年纪，失落无考。后面又有一偈云：无才可去补苍天，枉入红尘若许年。此系身前身后事，倩谁记去作奇传？

But the name of the dynasty and the year of the reign were obliterated and could not be confirmed. There was also a Buddhist verse following behind:
Lacking in virtues to mend the azure skies,
in vain I have been into the mortal world for many years.
These facts are of a former and after life,
but who will record a strange legend for me?--[[User:Li Ruiyang|Li Ruiyang]] ([[User talk:Li Ruiyang|talk]]) 03:57, 24 November 2021 (UTC)

But the name of the dynasty and the year of the reign were obliterated and could not be confirmed. There was also a Buddhist verse following behind:
Lacking in virtues to mend the azure sky, nothing have I gained within the years spent in the secular world. All of these about my present life and afterlife, who would record them for me?--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 14:59, 26 November 2021 (UTC)

==李姗 Lǐ Shān 英语语言文学（英美文学）女 202120081498==

空空道人看了一回，晓得这石头有些来历，遂向石头说道：“石兄，你这一段故事，据你自己说来，有些趣味，故镌写在此，意欲闻世传奇。据我看来：第一件，无朝代年纪可考；第二件，并无大贤大忠理朝廷、治风俗的善政，其中只不过几个异样女子，或情或痴，或小才微善。我纵然抄去，也算不得一种奇书。”

As the Taoist priest named Kongkong once has examined the stone, he had some idea about the story on it, and then said to the stone, "Brother, maybe in your opinion, the story inscribed on you is of some interest so as to be kept here to win a fame throughout the world. But to my mind, it is far from a legend book to be transcribed. Firstly, there are hardly any clues about the time period of the background; secondly, no outstanding governance regarding politics and costumes has been achieved by great talents or loyal officials, and what it mainly narrates are merely several unusual women, some stuck in love, some boasting subtle intelligence and benevolence."--[[User:Li Shan|Li Shan]] ([[User talk:Li Shan|talk]]) 09:02, 21 November 2021 (UTC)

As the Taoist priest named Kongkong once has examined the stone, he knew that the stone had some history, and then said to the stone, "Brother, maybe in your opinion, the story inscribed on you is of some interest so as to be kept here to win a fame throughout the world. But to my mind, it is far from a legend book to be transcribed. Firstly, there are hardly any clues about the time period of the background; secondly, no outstanding governance regarding politics and costumes has been achieved by great talents or loyal officials, and what it mainly narrates are merely several unusual women, some stuck in love, some boasting subtle intelligence and benevolence."--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 03:05, 27 November 2021 (UTC)

==李双 Lǐ Shuāng 翻译学女 202120081499==

石头果然答道：“我师何必太痴？我想历来野史的朝代，无非假借汉、唐的名色；莫如我这石头所记，不借此套，只按自己的事体情理，反倒新鲜别致。况且那野史中，或讪谤君相，或贬人妻女，奸淫凶恶，不可胜数；更有一种风月笔墨，其淫秽污臭，最易坏人子弟。

The stone answered: “Why are you so stubborn? I think the dynasties of unofficial history are nothing more than under the guise of Han, Tang. They are not as good as the stories recorded by me, a stone, which don’t follow the convention but according to the real facts and therefore are more novel on the contrary. Moreover, those unofficial histories are either slandering the emperor and his subjects, or belittling other people’s wives and children. There are countless descriptions of ferocity and adultery which are the most likely to have a bad influence on the younger generation.”--[[User:Li Shuang|Li Shuang]] ([[User talk:Li Shuang|talk]]) 10:54, 24 November 2021 (UTC)

The stone answered: “Why are you so stubborn? I think the dynasties recorded in the unofficial histories are nothing more than under the guise of Han and Tang Dynasty. They are not as good as the stories recorded by me, a stone, which don’t follow the convention but according to the real facts and therefore are more novel on the contrary. Besides, those unofficial histories are either slandering the emperor and his subjects, or belittling other people’s wives and children. There are countless descriptions of ferocity and adultery which are most likely to have a bad influence on the younger generation.” --[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 11:10, 24 November 2021 (UTC)

==李文璇 Lǐ Wénxuán 英语语言文学（英美文学）女 202120081500==

至于才子佳人等书，则又开口文君，满篇子建，千部一腔，千人一面，且终不能不涉淫滥。在作者不过要写出自己的两首情诗艳赋来，故假捏出男女二人名姓；又必旁添一小人拨乱其间，如戏中小丑一般。更可厌者，之乎者也，非理即文，大不近情，自相矛盾。

As for the books about the talented and the beauties, they talked about Wen and Jun, the pages were also full of Zi and Jian. A thousand volumes present the same thing, and a thousand person are also in the same character. Moreover, they cannot avoid to some licentious things. The authors, who had to write several sentimental odes and elegant ballads, had falsely invented the names of both men and women, and also some bad guys who like a clown in a play made some troubles in there. As for the annoying men, they had nothing in their minds and talked about Li and Wen, which had no link with the targeted things and paradoxical in the whole.--[[User:Li Wenxuan|Li Wenxuan]] ([[User talk:Li Wenxuan|talk]]) 00:53, 22 November 2021 (UTC)
As for books related to talented scholars and beautiful ladies, he also talked about Wenjun, who is good at articles and is capricious, but he could not avoid prostitution in the end. The author just wants to write two of his own love poems, so he falsely pinches out the names of men and women; he must add a little person to make trouble in the meantime, like a clown in a play. The more annoying, the more it is, the unreasonable is the literary, the most unkind, self-contradictory.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 03:24, 24 November 2021 (UTC)

==李雯 Lǐ Wén 英语语言文学（英美文学）女 202120081501==

竟不如我这半世亲见亲闻的几个女子，虽不敢说强似前代书中所有之人，但观其事迹原委，亦可消愁破闷；至于几首歪诗，也可以喷饭供酒。其间离合悲欢，兴衰际遇，俱是按迹循踪，不敢稍加穿凿，至失其真。只愿世人当那醉馀睡醒之时，或避事消愁之际，把此一玩，不但是洗旧翻新，却也省了些寿命筋力，不更去谋虚逐妄了。
It’s not as good as the few women I’ve seen and heard about in this half of my life. Although I dare not say that she is better than all the people in the books of the previous generations. Looking at their deeds, you can also relieve your sorrow and boredom. As for a few poor poems, you can also taste them while eating and drinking.The joys and sorrows, the ups and downs all follow the traces, daring not to lose the truth. I only hope that when the world is awake, or when avoiding troubles and sorrows ,they can enjoy it, not only to renovate, but also to save some lifespan and energy, not to seek falsehood.--[[User:Li Wen|Li Wen]] ([[User talk:Li Wen|talk]]) 03:15, 24 November 2021 (UTC)

I am not as good as the women I have seen and heard in my life. Though I cannot say that they are as good as all the people in the books of previous generations, I can relieve my sorrow and despair by watching their deeds. As for a few crooked poems, you can also spray rice for wine. During the separation of joys and sorrows, ups and downs, are all traced, dare not slightly cut, to lose its true. I only hope that when people wake up from their drunkenness, or when they are relieved of their sorrow, they will not only wash the old and renew it, but also save some strength of life, so as not to seek for false things.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 04:39, 24 November 2021 (UTC)

==李新星 Lǐ Xīnxīng 亚非语言文学女 202120081503==

我师意为如何？”空空道人听如此说，思忖半晌，将这《石头记》再检阅一遍。因见上面大旨不过谈情，亦只是实录其事，绝无伤时诲淫之病，方从头至尾抄写回来，闻世传奇。
What do I mean?" Empty Taoist listen to say so, ponder a long time, will this "stone" review again. Seeing that the message above was only a talk of love, and only a record of it, without suffering from the disease of lewdness, I copied it back from beginning to end and heard the legend of the world.--[[User:Li Xinxing|Li Xinxing]] ([[User talk:Li Xinxing|talk]]) 04:38, 24 November 2021 (UTC)

What do I mean? " After hearing this, Taoist Kongkong thought for a long time and reviewed the stone story again. Seeing that the above general purpose is nothing but romance, it is only a factual record of its affairs, and there is no disease of obscenity at the time of injury, so I copied it back from beginning to end and heard the legend of the world.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 04:35, 24 November 2021 (UTC)

==李怡 Lǐ Yí 法语语言文学女 202120081504==

从此空空道人因空见色，由色生情，传情入色，自色悟空，遂改名情僧，改《石头记》为《情僧录》。东鲁孔梅溪题曰《风月宝鉴》。后因曹雪芹于悼红轩中披阅十载，增删五次，纂成目录，分出章回，又题曰《金陵十二钗》，并题一绝。
Since then empty Taoist empty because of empty see color, from color feeling, feeling into color, since color wukong, then changed the name of the monk, "stone" for "love monk record". Kong Meixi of The Eastern Lu dynasty wrote the book Fengyue Bao Jian. After cao Xueqin in mourning red xuan read ten years, add and delete five times, compiled into a directory, a chapter back, and the title yue ''Jinling twelve Hairpin'', and a must.--[[User:Li Yi|Li Yi]] ([[User talk:Li Yi|talk]]) 04:31, 24 November 2021 (UTC)

Since then Empty Taoist saw form through emptiness, generated emotions due to form, into which emptiness was stilled and epiphany was revealed, he then changed his epithet into Monk in Love, and changed ''The story of the Stone'' into ''Record of Monk in Love'', which was called ''Catalogue of Chinese Ancient Romance'' by Kong Meixi of The Eastern Lu dynasty. Afterwards Cao Xueqin read and amended it for ten years, revised and polished it for five times, and then compiled it into a directory with chapters and sections. Finally he entitled it ''The Twelve Flowers in Jinlin'' attached with a Chinese quatrain.--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 04:55, 24 November 2021 (UTC)

==刘沛婷 Liú Pèitíng 英语语言文学（英美文学）女 202120081505==

即此便是《石头记》的缘起。诗云：满纸荒唐言，一把辛酸泪。都云作者痴，谁解其中味?

This was the origin of ''The Story of The Stone''. A poem once said, “the whole novel is full of absurd words, as well as bitter tears. People all consider the author crazy, but is there anyone who knows its true meaning？--[[User:Liu Peiting|Liu Peiting]] ([[User talk:Liu Peiting|talk]]) 07:22, 23 November 2021 (UTC)

This is the origin of ''The Story of the Stone''. The poem says: The pages were full of idle words which was penned with hot and bitter tears; All men call the author fool, but no one understood his secret message.--[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 08:25, 23 November 2021 (UTC)

==刘胜楠 Liú Shèngnán 翻译学女 202120081506==

《石头记》缘起既明，正不知那石头上面记着何人何事？看官请听。按那石上书云：当日地陷东南，这东南有个姑苏城，城中阊门最是红尘中一二等富贵风流之地。

Now that the origin of the stone is clear, let us see what was written on the stone. Dear readers, please listen. Long ago, the earth dipped downwards in the southeast where there was a city named Gusu; and the quarter around Changmen Gate of Gusu was one of the most fashionable centres of wealth and nobility in the world of men. --[[User:Liu Shengnan|Liu Shengnan]] ([[User talk:Liu Shengnan|talk]]) 02:10, 23 November 2021 (UTC)

The origin of "The Story of the Stone" was clear, but did you know who or what was written on the stone? Please listen to me and go on. According to the record on the stone: One day, there was a subsidence in southeast and there was Gusu City. In the city, the quarter around Changmen Gate was one of the most fashionable centres of wealth and nobility in the world of men. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 03:13, 23 November 2021 (UTC)Liu Wei

==刘薇 Liú Wēi 国别女 202120081507==

这阊门外有个十里街，街内有个仁清巷，巷内有个古庙，因地方狭窄，人皆呼作“葫芦庙”。庙旁住着一家乡宦，姓甄名费，字士隐；嫡妻封氏，性情贤淑，深明礼义。家中虽不甚富贵，然本地也推他为望族了。

Outside the city of Changmen gate, there was a Shili street and a Renqing lane was on the street. In the Renqing lane, there was an ancient temple called "Hulu temple" owing to it`s narrow location. Next to the temple lived a hometown official named Zhen Fei, courtesy named Shi Yin; his legal wife, surnamed Feng, was a virtuous person with a deep sense of courtesy and righteousness. Although the family was not very rich, the local people also thought that he was a prominent family. --[[User:Liu Wei|Liu Wei]] ([[User talk:Liu Wei|talk]]) 14:02, 21 November 2021 (UTC)Liu Wei

Outside the Changmen gate was the Shili street and the Renqing lane, inside which was an ancient temple, called the "Gourd temple" for its narrow space. Next to the temple lived a retired official named Zhen Fei, whose courtesy name was Shi Yin; his legal wife Mrs. Feng was a virtuous person with a deep awareness of courtesy and righteousness. Although the family was not very rich, the locals also regarded him as a noble man.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 15:19, 22 November 2021 (UTC)

==刘晓 Liú Xiǎo 英语语言文学（英美文学）女 202120081508==

因这甄士隐禀性恬淡，不以功名为念，每日只以观花种竹、酌酒吟诗为乐，倒是神仙一流人物。只是一件不足：年过半百，膝下无儿；只有一女，乳名英莲，年方三岁。一日炎夏永昼，士隐于书房闲坐，手倦抛书，伏几盹睡，不觉矇眬中走至一处，不辨是何地方。

Hidden Truth had a tranquil mind, indifferent to fame or gain. The only fun in every day life was enjoying beautiful flowers and planting bamboo, drinking nectared wine and reciting poetry. What a fairy-like figure! There was only one pity, that is, though in his fifty years old, he had no son nut only one three-year-old daughter, named Pity Zhen. One day in the hot summer, Hidden Truth was sitting idly in his study. Tired, he threw away his book and fell asleep at his desk, drifting to a place he could not tell.--[[User:Liu Xiao|Liu Xiao]] ([[User talk:Liu Xiao|talk]]) 03:19, 21 November 2021 (UTC)

Zhen Shiyin had a tranquil mind, indifferent to fame or gain. The only fun in every day life was enjoying beautiful flowers and planting bamboo, drinking nectared wine and reciting poetry. What a fairy-like figure! But there was one pity, that is, though in his fifty years old, he had no son nut only one three-year-old daughter, named Yinglian. One day in the hot summer, Shenyin was sitting idly in his study. He was so tired that he threw away his book and fell asleep at his desk, drifting to a place he could not tell.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 05:12, 23 November 2021 (UTC)

==刘越 Liú Yuè 亚非语言文学女 202120081509==

忽见那厢来了一僧一道，且行且谈。只听道人问道：“你携了此物，意欲何往？”那僧笑道：“你放心。如今现有一段风流公案，正该了结，这一干风流冤家，尚未投胎人世。

Unexpectedly he espied， in the opposite direction， two priests coming towards him： the one a Buddhist， the other a Taoist. As they advanced they kept up the conversation in which they were engaged. "Whither do you purpose taking the object you have brought away？" he heard the Taoist inquire. To this question the Buddhist replied with a smile： "Set your mind at ease，" he said； "there's now in maturity a plot of a general character involving mundane pleasures， which will presently come to a denouement. The whole number of the votaries of voluptuousness have， as yet， not been quickened or entered the world.--[[User:Liu Yue|Liu Yue]] ([[User talk:Liu Yue|talk]]) 05:07, 23 November 2021 (UTC)

Unexpectedly he espied, from the opposite direction, A monk and a Taoist coming up to him. As they advanced, they kept up the conversation in which they were engaged. "Whither do you purpose taking the thing you have brought away？" He heard the Taoist inquire. The Buddhist replied with a smile: "Set your mind at ease. There's now a case of romantic affairs, which should presently come to a denouement. The whole number of the votaries of voluptuousness involved in have not been reincarnated.--[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:31, 24 November 2021 (UTC)

==刘运心 Liú Yùnxīn 英语语言文学（英美文学）女 202120081510==

趁此机会，就将此物夹带于中，使他去经历经历。”那道人道：“原来近日风流冤家又将造劫历世，但不知起于何处，落于何方？”那僧道：“此事说来好笑。

Taking this opportunity, we can mingle it in them and let it experience the life on earth." The Taoist said: "So those debtors of love affairs will be reincarnated and then suffer on earth. But from which place will the reincarnation start and in which direction will them be placed still remain unsettled." The monk said: "It's a funny story. --[[User:Liu Yunxin|Liu Yunxin]] ([[User talk:Liu Yunxin|talk]]) 12:28, 24 November 2021 (UTC)

Taking this opportunity, we can carry it away and let it experience the life on earth. ”The Taoist priest said: "The debtors of love affairs will be reincarnated and then suffer on earth recently. But it' s unknown that from when the story started and to where will it go.“ The monk said: "It's a funny story....-- --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 08:23, 28 November 2021 (UTC)

==罗安怡 Luó Ānyí 英语语言文学（英美文学）女 202120081511==

只因当年这个石头，娲皇未用，自己却也落得逍遥自在，各处去游玩。一日来到警幻仙子处，那仙子知他有些来历，因留他在赤霞宫中，名他为赤霞宫神瑛侍者。他却常在西方灵河岸上行走，看见那灵河岸上三生石畔有棵绛珠仙草，十分娇娜可爱，遂日以甘露灌溉，这绛珠草始得久延岁月。

This stone have not been used by The Empress Nu Wo. Thus It used to be free to roam on the heavens until one day he came to the Fairy of Wonders, who knew his special background. So she kept him in her palace and gave him the name by the Divine Eunuch of the Palace. He often walked along the bank of the Spirit River in the West where he saw a delicate and lovely flower on the bank of the Three Living Stones. Being struck with the great beauty of this flower, the stone remained there, tending its protegee with the most loving care, and daily moistening its roots with the choicest nectar of the sky. Yielding to the influence of disinterested love, the flower lived a longer life. --[[User:Luo Anyi|Luo Anyi]] ([[User talk:Luo Anyi|talk]]) 07:32, 28 November 2021 (UTC)

Because this stone in that age hasn‘t been used by a goddess in Chinese mythology，he could be careless and can go to visit many places for fun.One day，he come to the Fairy of Wonders who knew his special background. So she kept him in her palace and gave him the name by the Divine Eunuch of the Palace.But he always walks by the bank of the Spirit River.One day，he saw a fairy grass beside the Three Living Stones on the bank of the river，which is cute and delicate，so he irrigated it day by day，making it living longer.--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:31, 28 November 2021 (UTC)

==罗曦 Luó Xī 英语语言文学（英美文学）女 202120081512==

后来既受天地精华，复得甘露滋养，遂脱了草木之胎，幻化人形，仅仅修成女体，终日游于离恨天外，饥餐秘情果，渴饮灌愁水。只因尚未酬报灌溉之德，故甚至五内郁结着一段缠绵不尽之意。常说：‘自己受了他雨露之惠，我并无此水可还。
Afterwards，because of the essence of the nature and the nutrients of the dew，it gradually got rid of itself from the trees and become a human-being，but only can become a female，meandering outside all day long，when feeling hungry，she would eat fruits，and when feeling thirsty，she would drink water.The reason for her lingering emotions is that she haven‘t showed her gratitude to her benefactors.She always said that：“I was benefited from his dew，but I can‘t bring back a report.”--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:21, 28 November 2021 (UTC)--[[User:Luo Xi|Luo Xi]] ([[User talk:Luo Xi|talk]]) 15:21, 28 November 2021 (UTC)

==马新 Mǎ Xīn 外国语言学及应用语言学女 202120081513==

他若下世为人，我也同去走一遭，但把我一生所有的眼泪还他，也还得过了。’因此一事，就勾出多少风流冤家都要下凡，造历幻缘，那绛珠仙草也在其中。今日这石正该下世，我来特地将他仍带到警幻仙子案前，给他挂了号，同这些情鬼下凡，一了此案。”

If he could be reincarnated as human in the next life, I would also go with him but only in this time return all the sorrows to him, which can let me go through the life. “For this reason, how many pretty teases have to descend to the world suffering the illusory fates, and the Crimson Pearl Flower is also among them. Today, this stone is about to be born, so I comes here specially to bring him to the court of Fairy Maiden Jinhuan, registering him and letting him go down to the earth with ghosts in order to settle the case.”--[[User:Ma Xin|Ma Xin]] ([[User talk:Ma Xin|talk]]) 12:37, 24 November 2021 (UTC)

If he could be reincarnated as human in the next life, I would go with him, but I should also return all the sorrows in this time to him, which can enable me to go through the life. "For this reason, lots of pretty teases have to descend to the world suffering the illusory destiny, and that Crimson Pearl Flower is also amomg them. Today this jade is about to be born, so I come here specially to take him to the court of Fairy Maiden Jinhuan, endowing him with a registration and letting him go down to the earth with those sentimental ghosts so as to settle the case.--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 15:16, 27 November 2021 (UTC)

==毛雅文 Máo Yǎwén 英语语言文学（英美文学）女 202120081514==

那道人道：“果是好笑，从来不闻有‘还泪’之说。趁此，你我何不也下世度脱几个，岂不是一场功德？”那僧道：“正合吾意。你且同我到警幻仙子宫中，将这蠢物交割清楚，待这一干风流孽鬼下世，你我再去。如今有一半落尘，然犹未全集。”

The Taoist priest says:"It's really ridiculous. I have never heard of the saying of 'returning tears'. We can also take this opportunity to release several souls from purgatory (help several souls of the decease get rid of worldly sufferings). Isn't it a merit?" The monk replies:"It's exactly what I am hoping for. You and I are going to the palace of the fairy maiden Jing Huan, and to deliver such a jade and figure it out. When these dissolute and sinful evils all pass away, we will go to the afterlife. Half of them have fallen into the earthly world, but they have not yet gathered completely."--[[User:Mao Yawen|Mao Yawen]] ([[User talk:Mao Yawen|talk]]) 15:04, 27 November 2021 (UTC)

The Taoist priest says:"It's really ridiculous. I have never heard of the saying of 'returning tears'. We can also take this opportunity to release several souls from purgatory (help several souls of the decease get rid of worldly sufferings). Isn't it a merit?" The monk replies:"It's exactly what I am hoping for. You and I will go the palace of the fairy maiden Jing Huan, and to deliver such a jade and figure it out. When these dissolute and sinful evils all pass away, we will go to the afterlife. Half of them have fallen into the earthly world, but they have not yet gathered completely."--[[User:Mao You|Mao You]] ([[User talk:Mao You|talk]]) 06:56, 23 November 2021 (UTC)

==毛优 Máo Yōu 俄语语言文学女 202120081515==

道人道：“既如此，便随你去来。”却说甄士隐俱听得明白，遂不禁上前施礼，笑问道：“二位仙师请了。”那僧、道也忙答礼相问。

The Taoist said, "In that case, let's go with you." Then Hidden Truth heard and understood, so he could not help but go forward to salute, smiling and saying, " Please, distinguished masters." The monk and the Taoist also replied with manners.

The Taoist said, "In that case, let's go with you." Then Hidden Truth heard and understood, so he could not help but go forward to salute, smiling and saying, " Please, distinguished masters." The monk and the Taoist also immediately replied with manners.--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 10:50, 24 November 2021 (UTC)

==牟一心 Móu Yīxīn 英语语言文学（英美文学）女 202120081516==

士隐因说道：“适闻仙师所谈因果，实人世罕闻者。但弟子愚拙，不能洞悉明白。若蒙大开痴顽，备细一闻，弟子洗耳谛听，稍能警省，亦可免沉沦之苦了。”

Hidden Truth said: "What you master talked about the cause and effect is definitely rare in the world. But I am stupid and can't fully understand it. If you can explain it for me to get rid of infatuation and stubbornness, I will listen to you carefully and then take warning from it, avoiding the suffering of enthrallment."--[[User:Mou Yixin|Mou Yixin]] ([[User talk:Mou Yixin|talk]]) 08:01, 21 November 2021 (UTC)

Hidden Truth then said, "I have just heard you master's words about karma, a truly rare insight in the world. But I am too ignorant to understand it. If I could be enlightened by you two to get rid of infatuation and stubbornness, I would certainly listen carefully to all that you say and then take warning from it, avoiding the suffering of enthrallment."--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 07:54, 22 November 2021 (UTC)

==彭瑞雪 Péng Ruìxuě 法语语言文学女 202120081517==

二仙笑道：“此乃玄机，不可预泄。到那时只不要忘了我二人，便可跳出火坑矣。”士隐听了，不便再问，因笑道：“玄机固不可泄露，但适云‘蠢物’，不知为何？或可得见否？”那僧说：“若问此物，倒有一面之缘。”

The two immortals laughed and said, "It is something metaphysical and cannot be divulged in advance. At that time, just don't forget the two of us, and you will be free from your predicament." When Shi Yin heard this, he stopped pursuing the matter. He laughed and said, "Of course the mystery must not be divulged, but I don't quite understand what the 'stupid thing' is that you just mentioned. Perhaps I have a chance to see it?" The monk said, "This thing you are asking about, you do have the fortune to see it.--[[User:Peng Ruixue|Peng Ruixue]] ([[User talk:Peng Ruixue|talk]]) 07:39, 22 November 2021 (UTC)

The two immortals laughed and said, "It is metaphysical and cannot be divulged in advance. At that time, if you don't forget two of us, and you will be free from your predicament." When Shi Yin heard this, he stopped pursuing the matter. He laughed and said, "Of course the mystery must not be divulged, but I don't quite understand what the 'stupid thing' is that you just mentioned. Perhaps I have a chance to see it?" The monk said, "This thing you are asking about, you do have the fortune to see it.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 06:17, 29 November 2021 (UTC)

==秦建安 Qín Jiànān 外国语言学及应用语言学女 202120081518==

说着取出，递与士隐。士隐接了看时，原来是块鲜明美玉，上面字迹分明，镌着“通灵宝玉”四字，后面还有几行小字。正欲细看时，那僧便说已到幻境，就强从手中夺了去。

He said and took it out to Hidden Truth. ShiYin received it and found it a bright beautiful jade in which there were four clear characters:Tong Ling Bao Yu followes by several lines of words.When Hidden Truth craved for a careful look, that monk said that he had reached the illusion, so he snatched it from ShiYin's hand.--[[User:Qing Jianan|Qing Jianan]] ([[User talk:Qing Jianan|talk]]) 02:57, 21 November 2021 (UTC)

Then he said as he took it out and handed it to Hidden Truth. Hidden Truth took a look, and it turned out to be a piece of bright beautiful jade, with clear writing above, engraved with the “Tongling jade”. There were a few lines of small characters behind. When he was about to take a closer look, the monk said he had reached the Illusory Land and snatched the jade from his hands.--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 01:47, 22 November 2021 (UTC)

==邱婷婷 Qiū Tíngtíng 英语语言文学（语言学）女 202120081519==

和那道人竟过了一座大石牌坊，上面大书四字，乃是“太虚幻境”。两边又有一副对联道：假作真时真亦假，无为有处有还无。士隐意欲也跟着过去，方举步时，忽听一声霹雳，若山崩地陷。

And with that Taoist priest actually passed a large stone archway, above which was engraved four big words, is “ Illusory Land of Great Void ”.On both sides there was a pair of couplets: If false is taken as the truth, then truth is said to be lieing , when nothing is taken as being, then being itself is turned into nothing. Hidden Truth also wanted to pass the big stone archway, but the moment he was about to raise his foot, he heard a crack of thunder which sounded as if the hills were rending asunder and the earth falling in.--[[User:Qiu Tingting|Qiu Tingting]] ([[User talk:Qiu Tingting|talk]]) 02:52, 21 November 2021 (UTC)

And that Taoist passed a large stone pagoda, written on it four big words, is "Taixu fantasy realm". On both sides, there is a couplet saying: "Falsehood is true when it is true, and there is nothing where there is nothing". Hidden Truth also wanted to follow, when just ready to raise his feet, he heard a thunderbolt all of a sudden, as if a landslide happened.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 02:48, 21 November 2021 (UTC)

==饶金盈 Ráo Jīnyíng 英语语言文学（语言学）女 202120081520==

士隐大叫一声，定睛看时，只见烈日炎炎，芭蕉冉冉，梦中之事便忘了一半。又见奶母抱了英莲走来。士隐见女儿越发生得粉装玉琢，乖觉可喜，便伸手接来，抱在怀中，斗他玩耍一会。

Hidden Truth cried out, and when he fixed his eyes, only seeing the sun is shining, the weather is bright, and the plantains are flourishing, and then he forgot half of his dream. Later, the lactating mother coming with Pity Zhen in her arms. When Hidden Truth noted that his daughter was becoming more and more beautiful and cute, he reached out and took her in his arms, and teased her for a while.--[[User:Rao Jinying|Rao Jinying]] ([[User talk:Rao Jinying|talk]]) 02:43, 21 November 2021 (UTC)

Hidden Truth cried out, fixing his eyes on the blazing sun and supplely drooping banana leaves, only to be oblivious to half of his dream. Then the wet nurse came over with Pity Zhen in her arms. Hidden Truth perceived that his daughter became so fair and lovely that he couldn’t wait to cradle her in his arms to amuse her.--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 05:48, 21 November 2021 (UTC)

== Headline text ==
==石丽青 Shí Lìqīng 英语语言文学（英美文学）女 202120081521==

又带至街前，看那过会的热闹。方欲进来时，只见从那边来了一僧一道：那僧癞头跣足，那道跛足蓬头，疯疯癫癫，挥霍谈笑而至。及到了他门前，看见士隐抱着英莲，那僧便大哭起来，又向士隐道：“施主，你把这有命无运、累及爹娘之物抱在怀内作甚？”

Hidden Truth then took his lovely daughter out into the street to see the lively meeting. When he was about to enter the door, he saw a monk and a Taoist coming from the other side: the monk had ringworm on his head and no shoes or socks on his feet; the Taoist priest was characterized by lameness and untidy hair. They came over, crazy, talking and laughing. When they got to Hidden Truth’s door, seeing him holding Pity Zhen in his arms. The monk began to cry and said to Hidden Truth, “ Benefactor, why did you cradle such an ill-fated and encumbering child in your arms？”--[[User:Shi Liqing|Shi Liqing]] ([[User talk:Shi Liqing|talk]]) 01:35, 21 November 2021 (UTC)

Shiyin then took his lovely daughter to the street to see the lively agora. When he was about to enter the door, he saw a monk and a Taoist priest coming from the other side: the monk had ringworm on his head and no shoes or socks on his feet; the Taoist priest was characterized by lameness and untidy hair. They acted like a lunatic and came over,talking and laughing. When they got to Shiyin’s door, seeing him holding Yinglian in his arms. The monk began to cry and said to Shiyin, “ Benefactor, why did you cradle such an ill-fated and encumbering child in your arms？”--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 06:06, 21 November 2021 (UTC)

==孙雅诗 Sūn Yǎshī 外国语言学及应用语言学女 202120081522==

士隐听了，知是疯话，也不睬他。那僧还说：“舍我罢，舍我罢。”士隐不耐烦，便抱着女儿转身。

After listening to him,Shiyin knew that it's crazy words and ignored him.But the monk also said:"Give her to me,give her to me." Shiyin was impatient,so he held his daughter and turned to leave.--[[User:Sun Yashi|Sun Yashi]] ([[User talk:Sun Yashi|talk]]) 05:59, 21 November 2021 (UTC)

After listening to him, Hidden Truth knew that it was lunatic ravings and ignored him. But the monk complemented:"Give her to me, give her to me." Hidden Truth got impatient, so he embraced his daughter and turned around. --[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 12:14, 23 November 2021 (UTC)

==王李菲 Wáng Lǐfēi 英语语言文学（英美文学）女 202120081523==

才要进去，那僧乃指着他大笑，口内念了四句言词，道是：惯养娇生笑你痴，菱花空对雪澌澌。好防佳节元宵后，便是烟消火灭时。

When he was about to get in, the monk pointed at him and laughed, mumbling four sentences, which mean “how crazy that you pamper your daughter like this, (see you embrace Yinglian), just like the summer lotus are exposed to the winter snow. Beware of the days after the Lantern Festival, then there is a fire to vanish everything.”--[[User:Wang Lifei|Wang Lifei]] ([[User talk:Wang Lifei|talk]]) 03:03, 21 November 2021 (UTC)
When he wanted to go in, the monk pointed at him and laughed, saying…--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 06:56, 24 November 2021 (UTC)

==王逸凡 Wáng Yìfán 亚非语言文学女 202120081524==

士隐听得明白，心下犹豫，意欲问他来历，只听道人说道：“你我不必同行，就此分手，各干营生去罢。三劫后，我在北邙山等你，会齐了，同往太虚幻境销号。”那僧道：“最妙，最妙。”
Shi Yin understood and hesitated, intending to ask him where he came from. The Taoist said, "You and I don't need to go together. Three days later, I wait for you in north mangshan, meet together, with the imaginary land sales number." The monk said, "The best, the best."--[[User:Wang Yifan21|Wang Yifan21]] ([[User talk:Wang Yifan21|talk]]) 06:44, 24 November 2021 (UTC)

Shiyin understood,hesitated in his heart,and wanted to ask him where he came from.He only heard the Taoist say: "You and I don't have to go together, just break up and go to work. After the Three Tribulations, I will wait for you in Beimanshan,nnd go to the Tai Unreal Realm to sell the number." The monk said: "The most wonderful, the most wonderful."--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 13:40, 28 November 2021 (UTC)

==王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525==

说毕，二人一去，再不见个踪影了。士隐心中此时自忖：“这两个人必有来历，很该问他一问，如今后悔却已晚了。”这士隐正在痴想，忽见隔壁葫芦庙内寄居的一个穷儒，姓贾名化、表字时飞、别号雨村的走来。

After that,the two went away,and they were nowhere to be seen.Shiyin thought to himself at this moment: "These two people must have a history.It's time to ask him,but now it's too late to regret." Shiyin was thinking about it,but suddenly saw a poor scholar living in the Hulu temple next door whose first name is Jia,last name hua,Courtesy name Shifei,and another name Yucun came.--[[User:Wang Zhenlong|Wang Zhenlong]] ([[User talk:Wang Zhenlong|talk]]) 13:37, 28 November 2021 (UTC)

After saying that, the two went away, and there was no sign of them anymore. Shiyin thought to himself at this moment: "These two people surely had some backgrounds. I should have asked him, but it was too late to regret now." Shiyin was daydreaming, but suddenly saw a poor scholar living in the Hulu temple next door coming up. His first name is hua, last name is jia, secondary personal name is Shifei, and another name is Yucun.--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 14:46, 28 November 2021 (UTC)

==卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526==

这贾雨村原系湖州人氏，也是诗书仕宦之族。因他生于末世，父母祖宗根基已尽，人口衰丧，只剩得他一身一口。在家乡无益，因进京求取功名，再整基业。

Rainvillage Merchant was born in Huzhou and came from a family of Confucian scholars and officials. Because he was born in last phase of age, the roots of his ancestors had died out. Family declined, and left him alone. He found no benefit in hometown, so he went to Beijing to strive for fame and tried to make another solid foundation for family.--[[User:Wei Yiwen|Wei Yiwen]] ([[User talk:Wei Yiwen|talk]]) 03:10, 21 November 2021 (UTC)

Jia Yucun came from Huzhou and was born in a family of scholars and officials. However, because he was born in the last phase of the age, the root of his ancestors had died out and family declined, leaving him alone in the world. He found no benefit in hometown, so he went to Beijing to strive for success and fame and tried to make the revitalization of his family.--[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 04:46, 21 November 2021 (UTC)

==魏楚璇 Wèi Chǔxuán 英语语言文学（英美文学）女 202120081527==

自前岁来此，又淹蹇住了，暂寄庙中安身，每日卖文作字为生，故士隐常与他交接。当下雨村见了士隐，忙施礼陪笑道：“老先生倚门伫望，敢街市上有甚新闻么？”士隐笑道：“非也。适因小女啼哭，引他出来作耍。正是无聊的很，贾兄来得正好，请入小斋，彼此俱可消此永昼。”

Since arriving in Beijing the year before last, Jia Yuchun had led a hard life, living only in a temple. He wrote poems and articles in exchange for money every day, so Shiyin often often met with him. Once Yucun saw Shiyin, hurriedly saluted and said with a smile, " Sir, you are leaning on the door and looking at something. Is there any news in the market?" Shiyin smiled and said, "No. Just because my little girl cried, so I took her out to play. I am so bored now and you are so nice to appear in time. Please come into my study with me, so that we can both kill the boring time." --[[User:Wei Chuxuan|Wei Chuxuan]] ([[User talk:Wei Chuxuan|talk]]) 03:35, 21 November 2021 (UTC)

Since arriving in Beijing the year before last, Jia Yuchun found himself in difficult conditions and desperate straits. He lived only in a temple and made a living by writing in exchange for money every day, so Shiyin often met with him. At that moment, Yucun saw Shiyin, hurriedly saluted and said with smile, " An old gentleman as you, leaning on the door and looking at something, I wander that is there any news in the street?" Shiyin smiled and said, "Hardly, just because my little girl cried, so I take her out to play. I am so bored now and you‘ve come just at the right moment. Please come into my study, so that we can spend the long day together."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 14:13, 23 November 2021 (UTC)

==魏兆妍 Wèi Zhàoyán 英语语言文学（英美文学）女 202120081528==

说着，便令人送女儿进去。自携了雨村来至书房中，小童献茶。方谈得三五句话，忽家人飞报：“严老爷来拜。”

While he was talking, he asked someone to take his daughter back to her room. Then he took Yucun to his study, and a child offered a cup of tea for each of them. But just said a few words, suddenly the family member came quickly to say that "Master Yan came to visit."--[[User:Wei Zhaoyan|Wei Zhaoyan]] ([[User talk:Wei Zhaoyan|talk]]) 07:30, 23 November 2021 (UTC)

While talking, he asked someone to take his daughter back to her room. Then he took Yucun to his study, and a child offered a cup of tea for each of them. But just said a few words, suddenly the family member came quickly to say that "Master Yan came to visit." --[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 14:01, 24 November 2021 (UTC)

==吴婧悦 Wú Jìngyuè 俄语语言文学女 202120081529==

士隐慌忙起身谢道：“恕诓驾之罪。且请略坐，弟即来奉陪。”雨村起身也让道：“老先生请便。晚生乃常造之客，稍候何妨！”说着，士隐已出前厅去了。

Shiying stood up hurriedly and said, " Excuse me.Please sit for a moment first, and I will entertain you at once." Yucun also stood up and answered:" Old gentleman, you go. I often come to you here as a guest, wait a little while is not the matter!" Said, Shiying had walked out of the guest room.--[[User:Wu Jingyue|Wu Jingyue]] ([[User talk:Wu Jingyue|talk]]) 02:51, 21 November 2021 (UTC)
Shiyin hurriedly got up and thanked, "excuse the crime of cheating driving. Please sit down and my brother will accompany you." Yucun got up and said, "please help yourself, sir. My late life is a regular guest. Why not wait a minute!" said Shiyin, who had left the front hall.--[[User:Wu Yinghong|Wu Yinghong]] ([[User talk:Wu Yinghong|talk]]) 13:44, 22 November 2021 (UTC)

==吴映红 Wú Yìnghóng 日语语言文学女 202120081530==

这里雨村且翻弄诗籍解闷，忽听得窗外有女子嗽声。雨村遂起身往外一看，原来是一个丫鬟在那里掐花儿：生的仪容不俗，眉目清秀，虽无十分姿色，却也有动人之处。雨村不觉看得呆了。那甄家丫鬟掐了花儿，方欲走时，猛抬头见窗内有人：敝巾旧服，虽是贫窘，然生得腰圆背厚，面阔口方，更兼剑眉星眼，直鼻方腮。
Here in the rain village, I turned to poetry books to relieve my boredom. Suddenly I heard a woman coughing outside the window. Yucun then got up and looked out. It turned out that it was a servant girl pinching flowers there: Sheng's appearance was not vulgar and his eyebrows were beautiful. Although he was not very beautiful, he was also moving. Yucun was stunned. The Zhen servant girl pinched the flowers. When Fang was about to leave, she suddenly looked up and saw someone in the window: Although I was poor and embarrassed, I had a round waist, thick back, wide face and square mouth. I also had sword eyebrows, star eyes, straight nose and square cheeks.

Yuncun was reading poems to relieve his boredom, suddenly hearing a girl outside the window coughing. Yucun stood up and found a housemaid picking flowers: she was of good appearance and pretty features. Although she was not perfect, she had something touching. Yucun felt stunned. The girl had pinched the flowers and was about to leave when she suddenly raised her head and saw someone in the window. In rags, he had a round waist and a thick back, a wide face and a square mouth, with a sword eyebrow and star eyes, a straight nose and a square cheek.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 10:14, 24 November 2021 (UTC)

==肖毅瑶 Xiāo Yìyáo 英语语言文学（英美文学）女 202120081531==

这丫鬟忙转身回避，心下自想：“这人生的这样雄壮，却又这样褴褛。我家并无这样贫窘亲友，想他定是主人常说的什么贾雨村了。怪道又说他必非久困之人，每每有意帮助周济他，只是没什么机会。”如此一想，不免又回头一两次。雨村见他回头，便以为这女子心中有意于他，遂狂喜不禁，自谓此女子必是个巨眼英豪，风尘中之知己。
The housemaid turned away quickly and said to herself:” the man is so grand and ragged. I don’t have such deprived friends and relatives, thus he must be Rain Village Merchant that the master has mentioned frequently. It’s said that he will not be trapped in poverty for a long time. The master has meant to help him but doesn’t find a proper chance.” At the thought of this, she looked back for several times, which misled Rian Village to think the girl was attracted by him and felt very excited. He believed that the girl must have a pair of wisdom eye and was his true friend in difficulty.--[[User:Xiao Yiyao|Xiao Yiyao]] ([[User talk:Xiao Yiyao|talk]]) 02:16, 24 November 2021 (UTC)

The housemaid turned away hurriedly and thought to herself:” the man is so strong, but his clothes are shabby. I don’t have such deprived friends and relatives, thus he must be Jia Yucun that the master has mentioned frequently. It’s said that he will not be trapped in poverty for a long time. The master has always meant to help him but doesn’t find a proper chance.” At the thought of this, she looked back for several times, which misled Yu Cun to think the girl was attracted by him and felt very excited. He believed that the girl must have a good taste and was his true friend in difficulty.--[[User:Xie Jiafen|Xie Jiafen]] ([[User talk:Xie Jiafen|talk]]) 11:27, 24 November 2021 (UTC)

==谢佳芬 Xiè Jiāfēn 英语语言文学（英美文学）女 202120081532==

一时小童进来，雨村打听得前面留饭，不可久待，遂从夹道中，自便门出去了。士隐待客既散，知雨村已去，便也不去再邀。一日，到了中秋佳节。

When a child came in, yucun heard that the host entertained the guests meal. Therefore, he knew that he couldn't stay long, so he went out through the lane and went out by himself. Later, Shiyin had already served guests, knowing that yucun had gone, so he didn't invite again. One day, it was the Mid Autumn Festival.

When a child came in, Yucun heard that the host entertained the guests meal. Therefore, he knew that he couldn't stay long, so he went out through the lane and went out by himself. Later, Shiyin had already served guests, knowing that yucun had gone, so he didn't invite again. One day, it was the Mid Autumn Festival.--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:53, 26 November 2021 (UTC)

==谢庆琳 Xiè Qìnglín 俄语语言文学女 202120081533==

士隐家宴已毕，又另具一席于书房，自己步至庙中来邀雨村。原来雨村自那日见了甄家丫鬟曾回顾他两次，自谓是个知己，便时刻放在心上。今又正值中秋，不免对月有怀，因而口占五言一律云：

Shiiyin‘s family banquet has been completed, and another seat in the study, he came to the temple to invite Yucun. It turns out that since that day Yucun saw the Zhen family maid had looked back at him twice, since he said he was a confidant, so he always put on his heart. Now it was the mid-autumn festival, so I couldn't help but feel nostalgic for the moon, so I took five words from the mouth and said.--[[User:Xie Qinglin|Xie Qinglin]] ([[User talk:Xie Qinglin|talk]]) 07:51, 26 November 2021 (UTC)

Shiiyin‘s family banquet has been completed, and another seat in the study, he came to the temple to invite Yucun. It turns out that since that day Yucun saw the Zhen family maid had looked back at him twice, since he said he was a confidant, so he always put on his heart. Now it was the mid-autumn festival, so I couldn't help but feel nostalgic for the moon, so I took five words from the mouth and said.--[[User:Xiong Min|Xiong Min]] ([[User talk:Xiong Min|talk]]) 14:30, 28 November 2021 (UTC)

==熊敏 Xióng Mǐn 英语语言文学（英美文学）女 202120081534==

未卜三生愿，频添一段愁。闷来时敛额，行去几回头。自顾风前影，谁堪月下俦？蟾光如有意，先上玉人楼。

I haven’t realized my dream yet, but had sorrowful experience. I often frown when I feel depressed and look back repeatedly when I farewell. With the wind blowing, I look at my shadow. Who can be my partner? If the moon helps,please shed light on the girl’s window and show her my love.

I haven’t realized my dream yet, but had sorrowful experience. I often frown when I feel depressed and look back repeatedly when I farewell. With the wind blowing, I look at my shadow. Who can be my partner? If the moon helps,please shed light on the girl’s window and show her my love.--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 12:02, 28 November 2021 (UTC)

==徐敏赟 Xú Mǐnyūn 语言智能与跨文化传播研究男 202120081535==

雨村吟罢，因又思及平生抱负，苦未逢时，乃又搔首对天长叹，复高吟一联云：玉在椟中求善价，钗于奁内待时飞。恰值士隐走来听见，笑道：“雨村兄真抱负不凡也！”

After Yucun finished reciting the love poems of Jiao Xing, he thought of his great ambitions and thought that he had not met a good time, so he recited a pair of couplets that he created aloud: "Jade and hairpin are all placed in the box, hoping that one day it can realize its value and play its role." Just when Shiyin came to hear it, Shiyin smiled and said, "Brother Yucun is really ambitious!"--[[User:Xu Minyun|Xu Minyun]] ([[User talk:Xu Minyun|talk]]) 11:38, 24 November 2021 (UTC)

After Yucun finished reciting the love poems of Jiao Xing, he thought of his great ambitions and thought that he had not met a good time, so he recited aloud a pair of couplets that he created: "Jade and hairpin are all placed in the box, hoping that one day it can realize its value and play its role." Just when Shiyin came to hear it, Shiyin smiled and said, "Yucun is really ambitious!"--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 16:53, 28 November 2021 (UTC)

==颜静 Yán Jìng 语言智能与跨文化传播研究女 202120081536==

雨村忙笑道：“不敢。不过偶吟前人之句，何期过誉如此！”因问：“老先生何兴至此？”士隐笑道：“今夜中秋，俗谓团圆之节。想尊兄旅寄僧房，不无寂寥之感。故特具小酌，邀兄到敝斋一饮。不知可纳芹意否？”

Yucun laughed and hurriedly said, "No no, I just recite the words of the predecessors. You speak too highly of me!" he asked, "Why did you come here, sir?" Shiyin smiled, "Tonight is the reunion time of Mid Autumn Festival. You lodged with a monk's room alone. So I come to invite you to have a drink with me. What do you think?"--[[User:Yan Jing|Yan Jing]] ([[User talk:Yan Jing|talk]]) 10:51, 21 November 2021 (UTC)

"Why did you come here, master?"
You are lodged with a monk's room alone. --[[User:Yan Lili|Yan Lili]] ([[User talk:Yan Lili|talk]]) 02:18, 29 December 2021 (UTC)

==颜莉莉 Yán Lìlì 国别女 202120081537==

雨村听了，并不推辞，便笑道：“既蒙谬爱，何敢拂此盛情！”说着，便同士隐复过这边书院中来了。须臾茶毕，早已设下杯盘，那美酒佳肴，自不必说。

Hearing this, Rainvillage Merchant did not refuse, but said with a smile: "Since I am indebted to you, I dare not live up to this feeling." Then he and Hidden Truth came to the academy here. In a moment they had finished their tea, and a feast had already been set up, with wine and food, in which the delicacy was all.

They went to the court in front of Hidden Truth 's study. Soon they had fin rished their tea and sat down to a collation of choice wine and delicacies.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 11:36, 28 November 2021 (UTC)

==颜子涵 Yán Zǐhán 国别女 202120081538==

二人归坐，先是款酌慢饮；渐次谈至兴浓，不觉飞觥献斝起来。当时街坊上家家箫管，户户笙歌；当头一轮明月，飞彩凝辉。二人愈添豪兴，酒到杯干。

At first, they drank slowly,but their spirits rose as they talked and they began to drink more recklessly. At that time, Flutes and strings can be heard everywhere and every family in the neighborhood was singing; When a bright moon rises, The two became more and more cheerful, and the wine dried cup up.--[[User:Yan Zihan|Yan Zihan]] ([[User talk:Yan Zihan|talk]]) 14:26, 27 November 2021 (UTC)

At first, they drank slowly,but their spirits rose as they talked in depth， they began to drink more recklessly. At that time, the sound of flutes and strings can be heard everywhere and every family in the neighborhood was playing and singing; When a bright moon rises, The two became more and more cheerful and drained cup after cup.--[[User:Yang Jiaying|Yang Jiaying]] ([[User talk:Yang Jiaying|talk]]) 11:39, 28 November 2021 (UTC)

==阳佳颖 Yáng Jiāyǐng 国别女 202120081540==

雨村此时已有七八分酒意，狂兴不禁，乃对月寓怀，口占一绝云：时逢三五便团圆，满把清光护玉栏。天上一轮才捧出，人间万姓仰头看。士隐听了，大叫：“妙极！弟每谓兄必非久居人下者，今所吟之句，飞腾之兆已现，不日可接履于云霄之上了。可贺，可贺！”

WE Rainvillage Merchant, eight-tenths drunk, cannot suppress his high spirits. As he gazed at the moon, he fostered thoughts, to which he gave vent by the recital of a double couplet.

"On the fifteenth the moon is full, Her pure rays fill the court; As her bright orb sails up the sky, All men on earth gaze upwards at the sight."

"Excellent!" cried Hidden Truth with a loud voice, after he had heard these lines; "I have repeatedly maintained that it was impossible for you to remain in a subordinate position for a long period, and now the verses are a prognostic of your rapid advancement. In a few days you will extend your footsteps far above the clouds! Let me congratulate you."！

WE Rainvillage Merchant, eight-tenths drunk, cannot suppress his elation. As he gazed at the moon, he improvised a poetry to the moon and declaimed it:

"On the fifteenth the moon is full, Her pure rays fill the court; As her bright orb sails up the sky, All men on earth gaze upwards at the sight."

"Excellent!" cried Hidden Truth with a loud voice, after he had heard these lines; "I have repeatedly maintained that it was impossible for you to remain in a subordinate position for a long period, and now the verses reveals your rapid advancement. In a few days you will extend your footsteps far above the clouds! Let me congratulate you."！--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 04:36, 28 November 2021 (UTC)

==杨爱江 Yáng Àijiāng 英语语言文学（语言学）女 202120081541==

乃亲斟一斗为贺。雨村饮干，忽叹道：“非晚生酒后狂言，若论时尚之学，晚生也或可去充数挂名。只是如今行李路费，一概无措，神京路远，非赖卖字撰文，即能到得。”士隐不待说完，便道：“兄何不早言？弟已久有此意，但每遇兄时，并未谈及，故未敢唐突。今既如此，弟虽不才，‘义利’二字，却还识得。且喜明岁正当大比，兄宜作速入都，春闱一捷，方不负兄之所学。其盘费馀事，弟自代为处置，亦不枉兄之谬识矣。”

Shiyin filled another large cup of alcohol. Yucun tossed it off and then signed. "Don't think this is just a talk after being drunk," he said, "I'm sure I could acquit myself quite creditably in the examinations, but I have no money in my wallet for my travelling expenses and the capital is far away. I can't raise enough money by selling my words and articles ...." "Why didn't you say so before?" interjected Shiyin. "I've always thought about this, but since you never mentioned it it is inappropriate for me to mention this subject. If that's how things are, dull as I am at least I know what's due to a firend. Luckily the Metropolitan Examinations are coming up next year. You must go as fast as you can to the capital and prove your learning in the Spring Test. I shall take it an honor to take care of the travelling expenses and other business for you."--[[User:Yang Aijiang|Yang Aijiang]] ([[User talk:Yang Aijiang|talk]]) 04:28, 28 November 2021 (UTC)

Hidden Truth filled another large cup of alcohol for congratulation. Rainvillage Merchant tossed it off and then sighed: "Don't think this is just a talk after drinking. I'm sure I could acquit myself quite creditably in the examinations, but I have no money in my wallet for my travelling expenses and the capital is far away. I can't raise enough money only by selling my words and articles ...." "Why didn't you say that before?" interjected Hidden Truth. "I've always thought about this, but since you never mentioned it.It is inappropriate for me to mention this subject. If that's how things are, dull as I am at least I know what's due to a real friend. Luckily the Metropolitan Examinations are coming up next year. You must go as fast as you can to the capital and prove your learning in the Spring Test. I shall take it an honor to take care of the travelling expenses and other business for you."--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 11:43, 28 November 2021 (UTC)

==杨堃 Yáng Kūn 法语语言文学女 202120081542==

当下即命小童进去，速封五十两白银并两套冬衣。又云：“十九日乃黄道之期，兄可即买舟西上。待雄飞高举，明冬再晤，岂非大快之事！”雨村收了银、衣，不过略谢一语，并不介意，仍是吃酒谈笑。

Hidden Truth immediately ordered the child to go in and quickly seal fifty liang silver and two sets of winter clothes. And he also said, "the 19th of March is the time of the zodiac, and you can buy a boat to the west. Isn't it a great pleasure to wait for triumph of the war[1] and meet again the next winter?" Rainvillage Merchant received the silver and clothes, but he thanked Hidden Truth a little. He didn't mind and was still drinking wine, talking and laughing.

[1]The war between Li Zicheng and the emperor Chongzhen. On March 19 of the lunar calendar in 1644, Emperor Chongzhen of the Ming Dynasty hanged himself. Then, Li Zicheng entered Beijing to overthrow the Ming Dynasty.--[[User:Yang Kun|Yang Kun]] ([[User talk:Yang Kun|talk]]) 03:23, 21 November 2021 (UTC)

Shiyin immediately ordered the child in and seal fifty liang silver and two suits of winter clothes quickly. Then he said, "the 19th of March is favorable time, and you can buy a boat to the west. Isn't it a great pleasure to wait for triumph of the war[1] and meet again the next winter?" Yucun received the silver and clothes, but he thanked Shiyin a little. He didn't mind and was still drinking wine, talking and laughing.

[1]The war between Li Zicheng and the emperor Chongzhen. On March 19 of the lunar calendar in 1644, Emperor Chongzhen of the Ming Dynasty hanged himself. Then, Li Zicheng entered Beijing to overthrow the Ming Dynasty.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 12:15, 23 November 2021 (UTC)

==杨柳青 Yáng Liǔqīng 英语语言文学（英美文学）女 202120081543==

那天已交三鼓，二人方散。士隐送雨村去后，回房一觉，直至红日三竿方醒。因思昨夜之事，意欲写荐书两封与雨村，带至都中去，使雨村投谒个仕宦之家，为寄身之地。

Jia Yunchun and Zhen Shiyin drank until midnight and then dispersed. Zhen Shiyin sent Jia Yuchun bedchamber and went back his room to sleep. He didn't wake up until the late morning. Considering Zhen Shiyin's bad conditions, Zhen Shiyin intended to write two recommendation letters for Jia Yuchun, so Jia Yuchun could take and deliver it to a family of dignities in Qi Zhou city to find a place to stay.--[[User:Yang Liuqing|Yang Liuqing]] ([[User talk:Yang Liuqing|talk]]) 06:10, 25 November 2021 (UTC)

These two friends drank until midnight and then left. Zhen Shiyin sent Jia Yuchun back to his bedchamber and headed back to sleep. He didn't wake up until the noon time. Zhen Shiyin intended to write two recommendation letters for Jia Yuchun considering his bad condition, so Jia Yuchun could take and deliver it to some family of dignities in Qi Zhou city to find a fine place to settle.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 05:11, 29 November 2021 (UTC)

==叶维杰 Yè Wéijié 国别男 202120081544==

因使人过去请时，那家人回来说：“和尚说：贾爷今日五鼓已进京去了，也曾留下话与和尚转达老爷，说：‘读书人不在黄道黑道，总以事理为要，不及面辞了。’”士隐听了，也只得罢了。真是闲处光阴易过，倏忽又是元宵佳节。

The family came back and said, “The monk said: The Five Drums of Master Jia has entered Beijing today, and he also left a message with the monk to convey to the master, saying:'The scholar is not in the zodiacal and underworld, and he always takes affair as the priority. , It's too late to resign.'" Shiyin listened and had no choice but to leave. It's really easy to spend leisure time, and suddenly it is the Lantern Festival.--[[User:Ye Weijie|Ye Weijie]] ([[User talk:Ye Weijie|talk]]) 13:21, 28 November 2021 (UTC)

When the family came back, they said, "The monk said that Master Merchant had gone to the capital between three and five o'clock today, and had left a message for the monk to convey to you, saying, 'No matter what the background of a scholar is, it is always important to take care of things, so it is too late to say goodbye.'" When Hidden Truth heard this, he had no choice but to do nothing. It was easy to spend time at leisure, and suddenly it was the Lantern Festival again.--[[User:Yi Yangfan|Yi Yangfan]] ([[User talk:Yi Yangfan|talk]]) 13:36, 28 November 2021 (UTC)Yi Yangfan

==易扬帆 Yì Yángfān 英语语言文学（英美文学）女 202120081545==

士隐令家人霍启抱了英莲，去看社火花灯。半夜中霍启因要小解，便将英莲放在一家门槛上坐着。待他小解完了来抱时，那有英莲的踪影。

Zhen Shiyin asked his family member Huo Qi to carry Yinglian and go to see the lanterns. In the middle of the night, Huo Qi had to take a piss, so he left Yinglian sitting on the threshold of a door. When he came to carry her after taking a piss, there was no sign of Yinglian.

Hidden Truth asked his family member trouble beginner to carry Pity Zhen and go to see the lanterns. In the middle of the night, trouble beginner left Pity Zhen alone sitting on the threshold of a door because of the urgency of urinating. When he came back, Pity Zhen disappeared.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 09:11, 27 November 2021 (UTC)

==殷慧珍 Yīn Huìzhēn 英语语言文学（英美文学）女 202120081546==

急的霍启直寻了半夜，至天明不见。那霍启也不敢回来见主人，便逃往他乡去了。那士隐夫妇见女儿一夜不归，便知有些不好。再使几人去找寻，回来皆云影响全无。

Huo Qi was so anxious that he looked for her all night and did not find her by dawn. So he did not dare to return to meet the host and he fled to his hometown. Mr. and Mrs. Shi Yin felt something is about to go wrong when they found their daughter didn't go home all night. They sent more people to look for her, but when they came back they said they didn't have any trace of her.--[[User:Yin Huizhen|Yin Huizhen]] ([[User talk:Yin Huizhen|talk]]) 14:22, 21 November 2021 (UTC)

Being so anxious, Huo Qi looked for her all night but in vain till dawn. Dare not to return to his master, he fled to another place. Mr. and Mrs. Shi Yin felt something wrong when their daughter didn't go home all night. More people were sent to look for her, but only to find no trace of her.--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:11, 22 November 2021 (UTC)

==殷美达 Yīn Měidá 英语语言文学（语言学）女 202120081547==

夫妻二人半世只生此女，一旦失去，何等烦恼，因此昼夜啼哭，几乎不顾性命。看看一月，士隐已先得病，夫人封氏也因思女搆疾，日日请医问卦。不想这日三月十五，葫芦庙中炸供，那和尚不小心，油锅火逸，便烧着窗纸。

The couple, having spent half of their lifetime, couldn't bear the thought of losing their only child. They wept day and night, almost risking their lives. In January, Shi Yin was already sick, and his wife Feng shi also fell ill for missing her daughter excessively and had to see doctors and fortunetellers everyday. Unfortunately, on March 15, when frying tributes in the calabash Temple, the careless monk let the fire escape from the oil boiler, which set the window paper on fire.--[[User:Yin Meida|Yin Meida]] ([[User talk:Yin Meida|talk]]) 14:57, 22 November 2021 (UTC)

The couple, having spent half of their lifetime, couldn't bear the annoyance of losing their only daughter. They wept all days and nights, almost risking their lives. In January, Hidden Truth was already sick, and his wife Feng also got ill for missing her daughter excessively and had to call the doctors and fortunetellers everyday. Unfortunately, on March 15, when frying tributes in the calabash Temple, the careless monk let the fire escape from the oil boiler, which set the window paper on fire.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 12:11, 28 November 2021 (UTC)

==尹媛 Yǐn Yuán 英语语言文学（英美文学）女 202120081548==

此方人家俱用竹篱木壁，也是劫数应当如此，于是接二连三，牵五挂四，将一条街烧得如火焰山一般。彼时虽有军民来救，那火已成了势了，如何救得下，直烧了一夜方熄，也不知烧了多少人家。只可怜甄家在隔壁，早成了一堆瓦砾场了，只有他夫妇并几个家人的性命不曾伤了，急的士隐惟跌足长叹而已。

This family deserves this fate for using bamboos and wood as hedge. One by one, the whole street burnt like the Mountain of Flames. At that time, though the army and people came for rescue, the fire had already been too large to put out. It didn't burn until the morning. It cannot be estimated that how many houses had been destroyed. Poor Hiden Truth's house next door had turned into a pile of rubble, only the couple and the families unhurt, which made Hidden Truth anxious and sigh deeply.--[[User:Yin Yuan|Yin Yuan]] ([[User talk:Yin Yuan|talk]]) 14:44, 22 November 2021 (UTC)

This family deserved this fate for using bamboos and wood as hedge. One house by one house, the whole street burnt like the Mountain of Flames. At that time, though the army and people came for rescue, the fire had already been too large to put out. It didn't burn until the morning. It cannot be estimated that how many houses had been destroyed. The fire had turned Poor Zhen's house next door into a pile of rubble, only the couple and several families unhurt, which made Zhen Shiyin anxious and sigh deeply.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 10:47, 24 November 2021 (UTC)

==詹若萱 Zhān Ruòxuān 英语语言文学（英美文学）女 202120081549==

与妻子商议，且到田庄上去住。偏值近年水旱不收，贼盗蜂起，官兵剿捕，田庄上又难以安身。只得将田地都折变了，携了妻子与两个丫鬟，投他岳丈家去。

He discussed with his wife, and went to live on the farm. However, in recent years, harvests have been ruined by flood and drought, and thieves and robbers have been rising. It was difficult to settle down on the farm. He had to sell his lands at a discount and took his wife and two maids to seek his father-in-law's help.--[[User:Zhan Ruoxuan|Zhan Ruoxuan]] ([[User talk:Zhan Ruoxuan|talk]]) 10:42, 24 November 2021 (UTC)
Take counsel with his wife, and come to live at the Grange. Partial value in recent years flood and drought do not harvest, thieves bee, officers and soldiers suppression, the grange and difficult to live. He had to change the land and went to his husband's house with his wife and two maids.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 12:22, 28 November 2021 (UTC)

==张秋怡 Zhāng Qiūyí 亚非语言文学女 202120081550==

他岳丈名唤封肃，本贯大如州人氏，虽是务农，家中却还殷实。今见女婿这等狼狈而来，心中便有些不乐。幸而士隐还有折变田产的银子在身边，拿出来托他随便置买些房地，以为后日衣食之计。

His father-in-law's name was Feng Su. His native place was Such State. Although he was a farmer, his family was well off. Now, seeing her son-in-law come in such a discomfiture, I felt unhappy. Fortunately, there are hidden converted field of silver in the side, took out to entrust him to buy some premises, that the day after the means of food and clothing.--[[User:Zhang Qiuyi|Zhang Qiuyi]] ([[User talk:Zhang Qiuyi|talk]]) 10:19, 21 November 2021 (UTC)

His father-in-law's name was Feng Su, who was originally from Daru State. Although he was a farmer, his family was well off. Now, seeing his son-in-law come in such a discomfiture, he felt unpleasant inside. Fortunately, there are hidden silver of converted field by his side, so he took it out to entrust him to purchase some premises for buying food and clothing in the future.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 11:40, 28 November 2021 (UTC)

==张扬 Zhāng Yáng 国别男 202120081551==

那封肃便半用半赚的，略与他些薄田破屋。士隐乃读书之人，不惯生理稼穑等事，勉强支持了一二年，越发穷了。封肃见面时，便说些现成话儿；且人前人后，又怨他不会过，只一味好吃懒做。

Feng Su made money while using some of it, and provided small fields and a shabby house with him. Shi Yin was a scholar and was not used to farming and other handworks. He reluctantly struggled for a year or two and became poorer and poorer. When Feng Su met him, he said something ready-made. But behind Shiyin's back, he complained that he couldn't live his life well by just being lazy.--[[User:Zhang Yang|Zhang Yang]] ([[User talk:Zhang Yang|talk]]) 11:34, 28 November 2021 (UTC)

Feng Su made money while using some of it, and provided small fields and a shabby house with him. Hidden Truth was a scholar and was not used to farming and other handworks. He reluctantly struggled for a year or two and became poorer and poorer. When Feng Su met him, he said something ready-made. But behind Shiyin's back, he complained that he couldn't live his life well by just being lazy.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 12:15, 28 November 2021 (UTC)

==张怡然 Zhāng Yírán 俄语语言文学女 202120081552==

士隐知道了，心中未免悔恨；再兼上年惊唬，急忿怨痛：暮年之人，那禁得贫病交攻，竟渐渐的露出那下世的光景来。可巧这日拄了拐，扎挣到街前散散心时，忽见那边来了一个跛足道人，疯狂落拓，麻鞋鹑衣，口内念着几句言词道：

When Hidden Truth found out about this, he felt remorse in his heart; he was also frightened of the previous year, and he felt angry and resentful: a man in his twilight years, who could not help being attacked by poverty and illness, was gradually revealing the scene of his next life. It happened that when he was on crutches, he went to the street for a walk, and suddenly he saw a crippled Taoist, crazy and untidy, with sackcloth shoes and quails, reciting a few words under his breath.--[[User:Zhang Yiran|Zhang Yiran]] ([[User talk:Zhang Yiran|talk]]) 02:26, 22 November 2021 (UTC)

When Hidden Truth found out this, he felt remorse in his heart; he was also frightened of the previous year, angry and resentful: a man in his twilight， who could not be able to be attacked by poverty and illness, was gradually revealing the scene of his next life. It happened that when he was on crutches, he went to the street for a walk, and suddenly he saw a crippled Taoist, crazy and untidy, with ragged shoes and clothes，reciting a few words under his breath.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 07:00, 22 November 2021 (UTC)

==钟义菲 Zhōng Yìfēi 英语语言文学（英美文学）女 202120081553==

世人都晓神仙好，惟有功名忘不了。古今将相在何方？荒冢一堆草没了。世人都晓神仙好，只有金银忘不了。终朝只恨聚无多，及到多时眼闭了。

The common people know that immortals are good, but they can't forget their achievements and fame. Where are the generals and prime ministers from ancient times to the present？What we can see are just deserted graves full of grass. The common people know that immortals are good, but they can‘t forget gold and silver. Till the end of life，they would regret their inability to create as much wealth as possible when they are alive and regret they are going to the heaven after they have accumulated plenty of wealth.--[[User:Zhong Yifei|Zhong Yifei]] ([[User talk:Zhong Yifei|talk]]) 02:42, 21 November 2021 (UTC)

All the common people know that immortals are good, but they can't forget their achievements and ambitions. Where are the great ones of old？They are just deserted graves full of grass. All the common people know that immortals are good, but they can‘t forget gold and silver. They grub for money all their lives until death seals up their eyes.--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 07:24, 21 November 2021 (UTC)

==钟雨露 Zhōng Yǔlù 英语语言文学（英美文学）女 202120081554==

世人都晓神仙好，只有姣妻忘不了。君生日日说恩情，君死又随人去了。世人都晓神仙好，只有儿孙忘不了。痴心父母古来多，孝顺子孙谁见了？

All men want to be immortals, but dote on the wives they’ve married. Those who swear to love their husband forever, but remarry as soon as he’s dead. All men want to be immortals, but dote on the sons they’ve gotten. Although infatuated parents are numerous, who ever saw really filial sons or daughters?--[[User:Zhong Yulu|Zhong Yulu]] ([[User talk:Zhong Yulu|talk]]) 02:05, 21 November 2021 (UTC)

Everyone in the world knows that the gods are good, but only the pretty wife can't forget. You swear to remember your husband’s kindness, but when your husband die, you go away with others. Everyone knows that the gods are good, but only the children and grandchildren cannot be forgotten. There are many loving parents in the past, but who has seen the filial children?--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 09:04, 22 November 2021 (UTC)

==周玖 Zhōu Jiǔ 英语语言文学（英美文学）女 202120081555==

士隐听了，便迎上来道：“你满口说些什么？只听见些‘好’、‘了’，‘好’、‘了’。”那道人笑道：“你若果听见‘好’、‘了’二字，还算你明白。可知世上万般，好便是了，了便是好：若不了，便不好；若要好，须是了。我这歌儿便叫《好了歌》。
When the hermit heard it, he came up and said, "What are you talking about ?" I just hear 'Hao’ (means good), 'Liao' (means end) 'Hao’, ‘Liao'. The man laughed, "If you hear the words 'Hao' and 'Liao', you understand it. In this world, good is end, and the end is good. If there is no end, there is no good, and vice versa. My song is called ‘The Song of ‘Hao’ and ‘ Liao’. ”--[[User:Zhou Jiu|Zhou Jiu]] ([[User talk:Zhou Jiu|talk]]) 08:54, 22 November 2021 (UTC)

Hidden Truth came over after heard this and said: “ What are you talking about? I just hear the words ‘good’ and ‘end’.” That man laughed, “ You heard the words ‘good’ and ‘end’, that means you got a few things going for you. In this world, good is end, and end is good. If there is no end, there is no good, and vice versa. My song is called ''All Dood Things Must End''.”--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 12:19, 22 November 2021 (UTC)

==周俊辉 Zhōu Jùnhuī 法语语言文学女 202120081556==

士隐本是有夙慧的，一闻此言，心中早已悟彻，因笑道：“且住，待我将你这《好了歌》注解出来何如？”道人笑道：“你就请解。”士隐乃说道：陋室空堂，当年笏满床。

So intelligent, Hidden Truth understood the essence of the song entirely in his head as soon as he heard it, and said: “ Wait a minute. How about I explain your song ''All Good Things Must End'' ？” The Taoist priest said, laughing : “ Would you please explain.” Hidden Truth then explain: “ The empty and dilapidated rattraps we see today, were the grand mansions full of beds and boards used by dignitaries at that time.”--[[User:Zhou Junhui|Zhou Junhui]] ([[User talk:Zhou Junhui|talk]]) 08:01, 22 November 2021 (UTC)

So intelligent as Hidden Truth is, he understood the essence of the song entirely in his head as soon as once hearing it, and said: “ Wait a minute. How about I explain your song ''All Good Things Must End'' ？” The Taoist priest said, laughing : “ Would you please explain.” Hidden Truth then explain: “ The empty and dilapidated rattraps we see today, were the grand mansions full of boards used by courtiers at that time.”--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:23, 23 November 2021 (UTC)

==周巧 Zhōu Qiǎo 英语语言文学（语言学）女 202120081557==

衰草枯杨，曾为歌舞场。蛛丝儿结满雕梁，绿纱今又在蓬窗上。说甚么脂正浓，粉正香，如何两鬓又成霜？
Humble hovels and abandoned halls where courtiers once paid daily calls；Bleak places where weeds and trees scarcely thrive
were once with a show of peace and prosperity．When cobwebs cover the mansion’s gilded beams，and collage casement with choice muslin gleams．Would you of perfumed elegance recite? Even as you speak, the raven locks turn white．--[[User:Zhou Qiao1|Zhou Qiao1]] ([[User talk:Zhou Qiao1|talk]]) 13:06, 23 November 2021 (UTC)

Withered grass and withered poplar, This used to be a place where people sang and danced. The spider silk is full of carved beams, but the green gauze is on the simple window. The fat is thick and the powder is fragrant, how the temples become the color of frost?--[[User:Zhou Qing|Zhou Qing]] ([[User talk:Zhou Qing|talk]]) 15:20, 25 November 2021 (UTC)

==周清 Zhōu Qīng 法语语言文学女 202120081558==

昨日黄土陇头埋白骨，今宵红绡帐底卧鸳鸯。金满箱，银满箱，转眼乞丐人皆谤。正叹他人命不长，那知自己归来丧。

Yesterday the bones were buried in the loess, and the mandarin ducks(allusions to couples) lie under the red silk tent tonight. Boxes full of gold, boxes full of silver, everyone yelled and insulted beggars in a blink of an eye. I'm sighing that the lives of others are not long, and I know I'm back to be mourned.

Yesterday the bones were buried in the loess, then tonight it is the time for a newly married couple to sleep behind bed curtains with burning red candle lights.Boxes full of gold, boxes full of silver, everyone yelled and insulted beggars in a blink of an eye. I'm sighed that the lives of others are not long, but failed to predict my own future after return from the funeral.--[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 11:36, 28 November 2021 (UTC)

==周小雪 Zhōu Xiǎoxuě 日语语言文学女 202120081559==

训有方，保不定日后作强梁；择膏粱，谁承望流落在烟花巷。因嫌纱帽小，致使锁枷扛；昨怜破袄寒，今嫌紫蟒长。乱烘烘，你方唱罢我登场，反认他乡是故乡。

Though she was well educated according to her parent's plan, one can become a bandit later. She tried her best to marry into a rich family. However, she ended up in a (red-light)? district beyond everyone's expectation. People who are not satisfied with their positions have to spend the rest of their life in a prison in chains. People who used to be very poor and used worn coats to resist the cold were not satisfied with fancy clothes after they became rich. I come on the stage as soon as you have finished your singing in a chaotic manner. Taking other's hometown as my own. --[[User:Zhou Xiaoxue|Zhou Xiaoxue]] ([[User talk:Zhou Xiaoxue|talk]]) 11:42, 22 November 2021 (UTC)--[[User:Mahzad Heydarian|Mahzad Heydarian]] ([[User talk:Mahzad Heydarian|talk]]) 16:56, 23 November 2021 (UTC)

If properly educated under parents' guidance, one can probabaly become a bandit later. Although trying her best to marry a rich man, she ends up with a driftage in the red-light district beyond everyone's expectation. People's unsatisfication with their positions leads to their miserable life in prison with chains on their bodies. People who used to be very poor and used worn coats to resist the cold were not satisfied with gorgeous clothes any more when they became rich. In noisy disorder, you just finished and I come on the scene.Instead, taking other's hometown as my own.--[[User:Zhu Suzhen|Zhu Suzhen]] ([[User talk:Zhu Suzhen|talk]]) 15:17, 25 November 2021 (UTC)

==朱素珍 Zhū Sùzhēn 英语语言文学（语言学）女 202120081561==

甚荒唐，到头来，都是为他人作嫁衣裳。那疯跛道人听了，拍掌大笑道：“解得切，解得切！”士隐便说一声：“走罢。”

It's so ridiculous. In the end, they made wedding clothes for others. Hearing this, the crazy lame Taoist clapped his hands and laughed, saying "All right, all right !" Then Shiyin said, "let's go."

It's ridiculous. In the end, they make wedding clothes for others. The crazy lame Taoist listened, clapped his hands and laughed and said, "it's right, it's right!" Shiyin said, "let's go."--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 11:43, 21 November 2021 (UTC)

== Headline text ==
==邹岳丽 Zōu Yuèlí 日语语言文学女 202120081562==

将道人肩上的搭裢抢过来背上，竟不回家，同着疯道人飘飘而去。当下哄动街坊，众人当作一件新闻传说。封氏闻知此信，哭个死去活来。

He grabbed the lap on the Taoist's shoulder and carried it on his back. He didn't go home and floated away with the crazy Taoist. At that moment, the neighborhood was stirred up and everyone regarded it as a news legend. When Feng heard this letter, he cried to death.--[[User:Zou Yueli|Zou Yueli]] ([[User talk:Zou Yueli|talk]]) 11:34, 21 November 2021 (UTC)

==Nadia 202011080004==

只得与父亲商议，遣人各处访寻，那讨音信。

==Mahzad Heydarian 玛莎 202021080004==

无奈何，只得依靠着他父母度日。

He was so helpless that he had to rely on his parents to survive.

==Mariam toure 2020GBJ002301==

幸而身边还有两个旧日的丫鬟伏侍，主仆三人，日夜作些针线，帮着父亲用度。

==Rouabah Soumaya 202121080001==

那封肃虽然每日抱怨，也无可奈何了。
Although Feng Su complained every day, he was helpless

==Muhammad Numan 202121080002==

这日那甄家的大丫鬟在门前买线，忽听得街上喝道之声。
The other day, the eldest maid of the Chen family was buying thread at the door when she heard a shout from the street.--[[User:Atta Ur Rahman|Atta Ur Rahman]] ([[User talk:Atta Ur Rahman|talk]]) 14:50, 23 November 2021 (UTC)

==Atta Ur Rahman 202121080003==

众人都说：“新太爷到任了。”
Everyone said: "The new grandfather has arrived"

==Muhammad Saqib Mehran 202121080004==

丫鬟隐在门内看时，只见军牢、快手一对一对过去，俄而大轿内抬着一个乌帽猩袍的官府来了。
When the maid concealed in the door, she saw the military jail and quick hands passing one by one, and the official mansion carrying a black hat and ape robe came in the big sedan chair.

==Zohaib Chand 202121080005==

那丫鬟倒发了个怔，自思：“这官儿好面善，倒像在那里见过的。”

<nowiki>Insert non-formatted text here</nowiki>
The maid was startled, and thought to herself: "This official is so good-natured, but it looks like someone I've seen there."

==Jawad Ahmad 202121080006==

于是进入房中，也就丢过，不在心上。

Then she went into the room and laid the matter aside ，without taking it to heart.

==Nizam Uddin 202121080007==

至晚间正待歇息之时，忽听一片声打的门响，许多人乱嚷，说：“本县太爷的差人来传人问话！”

English:
When I was about to rest in the evening, I heard a bang on the door suddenly, and many people shouted in disorder, saying, "The county's grandfather's messenger is here for questioning!"

==Öncü 202121080008==

封肃听了，唬得目瞪口呆。

Fengsu hear it,he gaped in consternation --[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 13:28, 22 November 2021 (UTC)

==Akira Jantarat 202121080009==

不知有何祸事，且听下回分解。

Don't know something calamity happened, will describe in the ensuing chapter.--[[User:AkiraJantarat|AkiraJantarat]] ([[User talk:AkiraJantarat|talk]]) 06:36, 21 November 2021 (UTC)

If you don't know what calamity took place, listen to the break down given in the next chapter.--[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 12:54, 21 November 2021 (UTC)

==Benjamin Wellsand 202111080118==

通灵──“通灵宝玉”的简称。Psychic--short for ''Psychic Treasure.--[[User:Benjamin Wellsand|Benjamin Wellsand]] ([[User talk:Benjamin Wellsand|talk]]) 12:48, 21 November 2021 (UTC)

Psychic -- the abbreviation for "Psychic Treasure". --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 03:35, 24 November 2021 (UTC)

==Asep Budiman 202111080020==

亦即下文所说女娲炼石补天所剩的那块“顽石”，因其历经锻炼而“灵性已通”，并能幻化为贾宝玉，故称。

That is to say, the "stubborn stone" left by Nüwa's refining stone to replenish the sky. As it has undergone training, it has "spiritual achievement" and can be transformed into Jia Baoyu, so it is called. --[[User:Asep Budiman|Asep Budiman]] ([[User talk:Asep Budiman|talk]]) 03:48, 24 November 2021 (UTC)

That is to say, the "stubborn stone" left by Nüwa's refining stone to replenish the sky, because it has undergone training, has "spiritually achieved" and can be transformed into Jia Baoyu, so it is called.--[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 06:10, 24 November 2021 (UTC)Ei Mon Kyaw

==Ei Mon Kyaw 202111080021==

《石头记》──此书的本名。
"Story of the Stone" - the original name of the book. --[[User:EIMONKYAW|EIMONKYAW]] ([[User talk:EIMONKYAW|talk]]) 06:26, 24 November 2021 (UTC)Ei Mon Kyaw

20211229 homework

2021-12-29T08:45:31Z

Wei Yiwen: /* 王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525 */

20211229 homework

2021-12-26T14:46:06Z

Wei Yiwen: /* 卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526 */

20211222 homework

2021-12-26T09:52:21Z

Wei Yiwen: /* 王镇隆 Wáng Zhènlóng 英语语言文学（英美文学）男 202120081525 */

20211222 homework

2021-12-22T02:14:22Z

Wei Yiwen: /* 卫怡雯 Wèi Yíwén 英语语言文学（英美文学）女 202120081526 */

Machine translation

2021-12-14T05:42:06Z

Wei Yiwen: /* Conclusion */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

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=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
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=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
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=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
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=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
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一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

[[Machine_Trans_EN_8]]

=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
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=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

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=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

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Networking Linking

http://www.elecfans.com/rengongzhineng/692245.html

https://baike.baidu.com/item/%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91/411793

=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
[[Machine_Trans_EN_13]]

=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
[[Machine_Trans_EN_14]]

===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpreters although it is quick and less time consuming.People are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translating word to word but it doesn't clarify it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical mistakes , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like anything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transferring researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation

The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation

When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is a challenge for human translators because it can reduce the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..

Machine translation

2021-12-14T05:41:06Z

Wei Yiwen: /* The advantages of human translation */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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[[Machine_Trans_EN_1]] [[Machine_Trans_EN_2]] [[Machine_Trans_EN_3]] [[Machine_Trans_EN_4]] [[Machine_Trans_EN_5]] [[Machine_Trans_EN_6]] [[Machine_Trans_EN_7]] [[Machine_Trans_EN_8]] [[Machine_Trans_EN_9]] [[Machine_Trans_EN_10]] [[Machine_Trans_EN_11]] [[Machine_Trans_EN_12]] [[Machine_Trans_EN_13]] [[Machine_Trans_EN_14]] [[Machine_Trans_EN_15]] [[Machine_Trans_EN_16]] [[Machine_Trans_EN_17]] [[Machine_Trans_EN_18]] [[Machine_Trans_EN_19]] [[Machine_Trans_EN_20]] [[Machine_Trans_EN_21]] [[Machine_Trans_EN_22]] [[Machine_Trans_EN_23]] [[Machine_Trans_EN_24]] [[Machine_Trans_EN_25]] [[Machine_Trans_EN_26]] [[Machine_Trans_EN_27]] [[Machine_Trans_EN_28]] [[Machine_Trans_EN_29]] [[Machine_Trans_EN_30]] ...

[[Book_projects|Back to translation project overview]]

[[DCG-To-Do|To the To Do list]]

=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

[[Machine_Trans_EN_1]]

=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
[[Machine_Trans_EN_3]]

=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
[[Machine_Trans_EN_5]]

=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
[[Machine_Trans_EN_6]]

=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
[[Machine_Trans_EN_7]]

一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

[[Machine_Trans_EN_8]]

=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
[[Machine_Trans_EN_9]]

=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

===Reference ===

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Zhuo Jianbin 卓键滨,Liu Wenxian 刘文娴,Peng Zili 彭子莉.机器翻译对各类型文本的德汉翻译能力探究[J][Research on the German Chinese Translation Ability of Machine Translation for Various Types of Texts]. Comparative Study of Cultural innovation 文化创新比较研究,2021,5(28):122-125.

(英) Peter Newmark A Textbook of Translation[M] Shanghai Foreign Education Press, 2002

Wang Hongqi 王红旗. (2008). 语言学概论 [Introduction to Linguistics]. Beijing: Peking University Press 北京大学出版社.

Liu Qin刘琴.功能目的论对于不同文本类型的翻译解读[J][Analysis of Translations in Different Types of Text based on Functionalist Approaches].Overseas Engliosh 海外英语,2021(17):8-9.

Zhang Peiji 张培基.英译中国现代散文选[M][Selected Modern Chinese Prose Writings]. Shanghai Foreign Languages Education Press 上海外语教育出版社, 2002.

Chen Cheng陈诚.机器翻译技术的综述[J][Overview of Machine Translation Technology].Electronic Techonology 电子技术,2021,50(11):290-291.

He Xinyu何馨宇.机器翻译的发展及其对翻译职业化的影响研究[J] [The Development of Machine Translation and its Effect on Professional Transltors].Overseas English 海外英语,2021(20):48-49.

He Wen 何雯, Wang Xiufeng 王秀峰.信息型文本的在线机器翻译错误研究[J][Research on Errors in Online Machine Translation of Informative text ].Overseas English海外英语,2021(15):188-189.

Li Hanji 李晗佶. (2021). 人工智能时代翻译技术与译者关系演变与重构 [Evolution and reconstruction of the relationship between translation technology and translators in the era of artificial intelligence]. 西华师范大学学报(哲学社会科学版) Journal of West China Normal University (PHILOSOPHY AND SOCIAL SCIENCES EDITION) (2021-12-04) 1-6.

Wei Guang魏光. 人工翻译与机器翻译译文编辑比较研究[J][Comparative Study of Translation Editing between Manual Translation and Machine Translation]. Overseas English 海外英语,2021(19):18-19+21.

=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

===References===
[1] Navroz Kaur Kahlon,(2021(prepublish));Williamjeet Singh.Machine translation from text to sign language: a systematic review[J].Universal Access in the Information Society,1-35.

[2] Cao Qianyu;Hao Hanmei,(2021);Ahmed Syed Hassan.A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis[J].Computational Intelligence and Neuroscience,3274326-3274326.

[3]Hwang Yongkeun;Kim Yanghoon;Jung Kyomin.(2021)Context-Aware Neural Machine Translation for Korean Honorific Expressions[J].Electronics,10(13):1589-1589.

[4]Zakaryia Almahasees.(2021)Analysing English-Arabic Machine Translation:Google Translate, Microsoft Translator and Sakhr.

[5](2021)Machine learning in translation[J].Nature Biomedical Engineering,5(6):485-486.

[6]Shaimaa Marzouk.(2021(prepublish))An in-depth analysis of the individual impact of controlled language rules on machine translation output: a mixed-methods approach[J].Machine Translation,1-37.

[7]Welnitzová Katarína;Munková Daša.(2021)Sentence-structure errors of machine translation into Slovak[J].Topics in Linguistics,22(1):78-92.

[8]Xu Xueyuan.(2021).Machine learning-based prediction of urban soil environment and corpus translation teaching[J].Arabian Journal of Geosciences,14(11).

[9]Chen Bingchang 陈丙昌(2016).機械翻訳の誤訳分析【D】.Error analysis of mechanical translation.贵州大学.2016(05)

[10]Lv Yinqiu 呂寅秋(1996).機械翻訳の言語規則と伝統文法との相違点.【D】The language rules of mechanical translation, the traditional grammar, and the points of contradiction.日本学研究.Japanese Studies.1996(00):21-22

[11]Liu Jun 刘君(2014).基于语料库的中日同形词词义用法对比及其日中机器翻译研究【D】.A Corpus-based Comparison of the Meanings of Chinese and Japanese Homographs and Research on Japanese-Chinese Machine Translation.广西大学.(03)

[12]Cun Qianqian 崔倩倩(2019).机器翻译错误与译后编辑策略研究【D】.Research on Machine Translation Errors and Post-Editing Strategies.北京外国语大学.(09)

[13]Zhang Yi 张义(2019).机器翻译的译文分析【D】.Translation analysis of machine translation.西安外国语大学.(10)

[14]Zhang Linqian 张琳婧(2019).在线机器翻译中日翻译错误原因及对策【D】.Causes and countermeasures of online machine translation errors in Chinese-Japanese translation.山西大学.(02)

[15]Wang Dan 王丹(2020).基于机器翻译的专利文本译后编辑对策研究【D】.Research on countermeasures for post-translational editing of patent texts based on machine translation.大连理工大学.(06)

[16]Yang Xiaokun 杨晓琨(2020).日中机器翻译中的前编辑规则与效果验证【D】.Pre-editing rules and effect verification in Japanese-Chinese machine translation.大连理工大学.(06)

[17]Zuo Jia 左嘉(2021). 机器翻译日译汉误译研究【D】. Research on Mistranslation of Machine Translation from Japanese to Chinese.北京第二外国语学院.

[18]Guan Biying 关碧莹(2018).关于政治类发言的汉日机器翻译误译分析【D】.Analysis of Chinese-Japanese Machine Translation Mistranslations of Political Speeches.哈尔滨理工大学.

[19]Che Tong 车彤(2021).汉译日机器翻译质量评估及译后编辑策略研究【D】.Research on Quality Evaluation of Chinese-Japanese Machine Translation and Post-translation Editing Strategies.北京外国语大学.(09)

Networking Linking

http://www.elecfans.com/rengongzhineng/692245.html

https://baike.baidu.com/item/%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91/411793

=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
[[Machine_Trans_EN_13]]

=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
[[Machine_Trans_EN_14]]

===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpreters although it is quick and less time consuming.People are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translating word to word but it doesn't clarify it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical mistakes , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like anything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transferring researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation

The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation

When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is challenge for human translators because it can reduces the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..

Machine translation

2021-12-14T05:34:55Z

Wei Yiwen: /* Body of article */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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[[Book_projects|Back to translation project overview]]

[[DCG-To-Do|To the To Do list]]

=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

[[Machine_Trans_EN_1]]

=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
[[Machine_Trans_EN_3]]

=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
[[Machine_Trans_EN_5]]

=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
[[Machine_Trans_EN_6]]

=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
[[Machine_Trans_EN_7]]

一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

[[Machine_Trans_EN_8]]

=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
[[Machine_Trans_EN_9]]

=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

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Zhang Peiji 张培基.英译中国现代散文选[M][Selected Modern Chinese Prose Writings]. Shanghai Foreign Languages Education Press 上海外语教育出版社, 2002.

Chen Cheng陈诚.机器翻译技术的综述[J][Overview of Machine Translation Technology].Electronic Techonology 电子技术,2021,50(11):290-291.

He Xinyu何馨宇.机器翻译的发展及其对翻译职业化的影响研究[J] [The Development of Machine Translation and its Effect on Professional Transltors].Overseas English 海外英语,2021(20):48-49.

He Wen 何雯, Wang Xiufeng 王秀峰.信息型文本的在线机器翻译错误研究[J][Research on Errors in Online Machine Translation of Informative text ].Overseas English海外英语,2021(15):188-189.

Li Hanji 李晗佶. (2021). 人工智能时代翻译技术与译者关系演变与重构 [Evolution and reconstruction of the relationship between translation technology and translators in the era of artificial intelligence]. 西华师范大学学报(哲学社会科学版) Journal of West China Normal University (PHILOSOPHY AND SOCIAL SCIENCES EDITION) (2021-12-04) 1-6.

Wei Guang魏光. 人工翻译与机器翻译译文编辑比较研究[J][Comparative Study of Translation Editing between Manual Translation and Machine Translation]. Overseas English 海外英语,2021(19):18-19+21.

=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

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[19]Che Tong 车彤(2021).汉译日机器翻译质量评估及译后编辑策略研究【D】.Research on Quality Evaluation of Chinese-Japanese Machine Translation and Post-translation Editing Strategies.北京外国语大学.(09)

Networking Linking

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=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
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=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
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===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpreters although it is quick and less time consuming.People are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translating word to word but it doesn't clarify it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical mistakes , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like anything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transferring researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation
The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation
When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is challenge for human translators because it can reduces the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..

Machine translation

2021-12-14T05:32:07Z

Wei Yiwen: /* Body of article */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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[[Book_projects|Back to translation project overview]]

[[DCG-To-Do|To the To Do list]]

=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

[[Machine_Trans_EN_1]]

=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
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=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
[[Machine_Trans_EN_5]]

=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
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=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
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一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

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=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
[[Machine_Trans_EN_9]]

=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

===Reference ===

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Zhuo Jianbin 卓键滨,Liu Wenxian 刘文娴,Peng Zili 彭子莉.机器翻译对各类型文本的德汉翻译能力探究[J][Research on the German Chinese Translation Ability of Machine Translation for Various Types of Texts]. Comparative Study of Cultural innovation 文化创新比较研究,2021,5(28):122-125.

(英) Peter Newmark A Textbook of Translation[M] Shanghai Foreign Education Press, 2002

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Liu Qin刘琴.功能目的论对于不同文本类型的翻译解读[J][Analysis of Translations in Different Types of Text based on Functionalist Approaches].Overseas Engliosh 海外英语,2021(17):8-9.

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Chen Cheng陈诚.机器翻译技术的综述[J][Overview of Machine Translation Technology].Electronic Techonology 电子技术,2021,50(11):290-291.

He Xinyu何馨宇.机器翻译的发展及其对翻译职业化的影响研究[J] [The Development of Machine Translation and its Effect on Professional Transltors].Overseas English 海外英语,2021(20):48-49.

He Wen 何雯, Wang Xiufeng 王秀峰.信息型文本的在线机器翻译错误研究[J][Research on Errors in Online Machine Translation of Informative text ].Overseas English海外英语,2021(15):188-189.

Li Hanji 李晗佶. (2021). 人工智能时代翻译技术与译者关系演变与重构 [Evolution and reconstruction of the relationship between translation technology and translators in the era of artificial intelligence]. 西华师范大学学报(哲学社会科学版) Journal of West China Normal University (PHILOSOPHY AND SOCIAL SCIENCES EDITION) (2021-12-04) 1-6.

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=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

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[2] Cao Qianyu;Hao Hanmei,(2021);Ahmed Syed Hassan.A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis[J].Computational Intelligence and Neuroscience,3274326-3274326.

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[7]Welnitzová Katarína;Munková Daša.(2021)Sentence-structure errors of machine translation into Slovak[J].Topics in Linguistics,22(1):78-92.

[8]Xu Xueyuan.(2021).Machine learning-based prediction of urban soil environment and corpus translation teaching[J].Arabian Journal of Geosciences,14(11).

[9]Chen Bingchang 陈丙昌(2016).機械翻訳の誤訳分析【D】.Error analysis of mechanical translation.贵州大学.2016(05)

[10]Lv Yinqiu 呂寅秋(1996).機械翻訳の言語規則と伝統文法との相違点.【D】The language rules of mechanical translation, the traditional grammar, and the points of contradiction.日本学研究.Japanese Studies.1996(00):21-22

[11]Liu Jun 刘君(2014).基于语料库的中日同形词词义用法对比及其日中机器翻译研究【D】.A Corpus-based Comparison of the Meanings of Chinese and Japanese Homographs and Research on Japanese-Chinese Machine Translation.广西大学.(03)

[12]Cun Qianqian 崔倩倩(2019).机器翻译错误与译后编辑策略研究【D】.Research on Machine Translation Errors and Post-Editing Strategies.北京外国语大学.(09)

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[15]Wang Dan 王丹(2020).基于机器翻译的专利文本译后编辑对策研究【D】.Research on countermeasures for post-translational editing of patent texts based on machine translation.大连理工大学.(06)

[16]Yang Xiaokun 杨晓琨(2020).日中机器翻译中的前编辑规则与效果验证【D】.Pre-editing rules and effect verification in Japanese-Chinese machine translation.大连理工大学.(06)

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[18]Guan Biying 关碧莹(2018).关于政治类发言的汉日机器翻译误译分析【D】.Analysis of Chinese-Japanese Machine Translation Mistranslations of Political Speeches.哈尔滨理工大学.

[19]Che Tong 车彤(2021).汉译日机器翻译质量评估及译后编辑策略研究【D】.Research on Quality Evaluation of Chinese-Japanese Machine Translation and Post-translation Editing Strategies.北京外国语大学.(09)

Networking Linking

http://www.elecfans.com/rengongzhineng/692245.html

https://baike.baidu.com/item/%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91/411793

=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
[[Machine_Trans_EN_13]]

=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
[[Machine_Trans_EN_14]]

===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpreters although it is quick and less time consuming.People are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translating word to word but it doesn't clarify it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical mistakes , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like anything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transfer researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, the World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation
The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation
When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is challenge for human translators because it can reduces the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..

Machine translation

2021-12-14T05:29:39Z

Wei Yiwen: /* Abstract */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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[[Machine_Trans_EN_1]] [[Machine_Trans_EN_2]] [[Machine_Trans_EN_3]] [[Machine_Trans_EN_4]] [[Machine_Trans_EN_5]] [[Machine_Trans_EN_6]] [[Machine_Trans_EN_7]] [[Machine_Trans_EN_8]] [[Machine_Trans_EN_9]] [[Machine_Trans_EN_10]] [[Machine_Trans_EN_11]] [[Machine_Trans_EN_12]] [[Machine_Trans_EN_13]] [[Machine_Trans_EN_14]] [[Machine_Trans_EN_15]] [[Machine_Trans_EN_16]] [[Machine_Trans_EN_17]] [[Machine_Trans_EN_18]] [[Machine_Trans_EN_19]] [[Machine_Trans_EN_20]] [[Machine_Trans_EN_21]] [[Machine_Trans_EN_22]] [[Machine_Trans_EN_23]] [[Machine_Trans_EN_24]] [[Machine_Trans_EN_25]] [[Machine_Trans_EN_26]] [[Machine_Trans_EN_27]] [[Machine_Trans_EN_28]] [[Machine_Trans_EN_29]] [[Machine_Trans_EN_30]] ...

[[Book_projects|Back to translation project overview]]

[[DCG-To-Do|To the To Do list]]

=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

[[Machine_Trans_EN_1]]

=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
[[Machine_Trans_EN_3]]

=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
[[Machine_Trans_EN_5]]

=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
[[Machine_Trans_EN_6]]

=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
[[Machine_Trans_EN_7]]

一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

[[Machine_Trans_EN_8]]

=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
[[Machine_Trans_EN_9]]

=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

===Reference ===

Cui Zihan 崔子涵.机器翻译译文质量对比——以谷歌翻译和DeepL为例[J] [Comparison among Machine Translation--Taking Google Translation and Deepl for Example].Overseas English 海外英语,2021(15):182-183.

Li Deyi 李德毅. (2018). 人工智能导论 [Introduction to Artificial Intelligence]. Beijing: China Science and Technology Press 中国科学技术出版社.

Qiu Quanju 仇全菊.大数据时代背景下机器翻译及其发展趋势[J][Machine Translation and its Development Trend under the Background of Big Data Era]. English Teachers 英语教师,2021,21(16):60-62.

Zhuo Jianbin 卓键滨,Liu Wenxian 刘文娴,Peng Zili 彭子莉.机器翻译对各类型文本的德汉翻译能力探究[J][Research on the German Chinese Translation Ability of Machine Translation for Various Types of Texts]. Comparative Study of Cultural innovation 文化创新比较研究,2021,5(28):122-125.

(英) Peter Newmark A Textbook of Translation[M] Shanghai Foreign Education Press, 2002

Wang Hongqi 王红旗. (2008). 语言学概论 [Introduction to Linguistics]. Beijing: Peking University Press 北京大学出版社.

Liu Qin刘琴.功能目的论对于不同文本类型的翻译解读[J][Analysis of Translations in Different Types of Text based on Functionalist Approaches].Overseas Engliosh 海外英语,2021(17):8-9.

Zhang Peiji 张培基.英译中国现代散文选[M][Selected Modern Chinese Prose Writings]. Shanghai Foreign Languages Education Press 上海外语教育出版社, 2002.

Chen Cheng陈诚.机器翻译技术的综述[J][Overview of Machine Translation Technology].Electronic Techonology 电子技术,2021,50(11):290-291.

He Xinyu何馨宇.机器翻译的发展及其对翻译职业化的影响研究[J] [The Development of Machine Translation and its Effect on Professional Transltors].Overseas English 海外英语,2021(20):48-49.

He Wen 何雯, Wang Xiufeng 王秀峰.信息型文本的在线机器翻译错误研究[J][Research on Errors in Online Machine Translation of Informative text ].Overseas English海外英语,2021(15):188-189.

Li Hanji 李晗佶. (2021). 人工智能时代翻译技术与译者关系演变与重构 [Evolution and reconstruction of the relationship between translation technology and translators in the era of artificial intelligence]. 西华师范大学学报(哲学社会科学版) Journal of West China Normal University (PHILOSOPHY AND SOCIAL SCIENCES EDITION) (2021-12-04) 1-6.

Wei Guang魏光. 人工翻译与机器翻译译文编辑比较研究[J][Comparative Study of Translation Editing between Manual Translation and Machine Translation]. Overseas English 海外英语,2021(19):18-19+21.

=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

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[11]Liu Jun 刘君(2014).基于语料库的中日同形词词义用法对比及其日中机器翻译研究【D】.A Corpus-based Comparison of the Meanings of Chinese and Japanese Homographs and Research on Japanese-Chinese Machine Translation.广西大学.(03)

[12]Cun Qianqian 崔倩倩(2019).机器翻译错误与译后编辑策略研究【D】.Research on Machine Translation Errors and Post-Editing Strategies.北京外国语大学.(09)

[13]Zhang Yi 张义(2019).机器翻译的译文分析【D】.Translation analysis of machine translation.西安外国语大学.(10)

[14]Zhang Linqian 张琳婧(2019).在线机器翻译中日翻译错误原因及对策【D】.Causes and countermeasures of online machine translation errors in Chinese-Japanese translation.山西大学.(02)

[15]Wang Dan 王丹(2020).基于机器翻译的专利文本译后编辑对策研究【D】.Research on countermeasures for post-translational editing of patent texts based on machine translation.大连理工大学.(06)

[16]Yang Xiaokun 杨晓琨(2020).日中机器翻译中的前编辑规则与效果验证【D】.Pre-editing rules and effect verification in Japanese-Chinese machine translation.大连理工大学.(06)

[17]Zuo Jia 左嘉(2021). 机器翻译日译汉误译研究【D】. Research on Mistranslation of Machine Translation from Japanese to Chinese.北京第二外国语学院.

[18]Guan Biying 关碧莹(2018).关于政治类发言的汉日机器翻译误译分析【D】.Analysis of Chinese-Japanese Machine Translation Mistranslations of Political Speeches.哈尔滨理工大学.

[19]Che Tong 车彤(2021).汉译日机器翻译质量评估及译后编辑策略研究【D】.Research on Quality Evaluation of Chinese-Japanese Machine Translation and Post-translation Editing Strategies.北京外国语大学.(09)

Networking Linking

http://www.elecfans.com/rengongzhineng/692245.html

https://baike.baidu.com/item/%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91/411793

=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
[[Machine_Trans_EN_13]]

=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
[[Machine_Trans_EN_14]]

===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpreters although it is quick and less time consuming.People are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translating word to word but it doesn't clarify it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical mistakes , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like everything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transfer researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, the World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation
The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation
When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is challenge for human translators because it can reduces the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..

Machine translation

2021-12-14T05:27:39Z

Wei Yiwen: /* Conclusion */

'''Machine Translation - A challenge or a chance for human translators?'''

[[Machine_translation|Overview Page of Machine Translation]]

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[[Book_projects|Back to translation project overview]]

[[DCG-To-Do|To the To Do list]]

=Chapter 1:A Comparison Between the Quality of Machine Translation and Human Translation——A Case Study of the Application of artificial intelligence in Sports Events=
'''论机器翻译与人工翻译的质量对比——以人工智能在体育赛事领域的应用为例'''

卫怡雯 Wei Yiwen, Hunan Normal University, China

[[Machine_Trans_EN_1]]

=Chapter 3：On the Realm Advantages And Mutual Development of Machine Translation And Huamn Translation)=
"'论机器翻译与人工翻译的领域优势及共同发展'"

肖毅瑶 Xiao Yiyao, Hunan Normal University, China
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=Chapter 4 : A Comparison Between Machine Translation of Netease and Traditional Human Translation—A Case Study of The Economist Articles)=
'''网易有道机器翻译与人工翻译的译文对比——以经济学人语料为例'''

王李菲 Wang Lifei, Hunan Normal University

[[Machine_Trans_EN_4]]

=Chapter 5: Muhammad Saqib Mehran - Problems in translation studies=
[[Machine_Trans_EN_5]]

=6 徐敏赟(Machine Translation Based on Neural Network --Challenge or Chance?)=
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=Chapter 7: The Cultivation of artificial intelligence and translation talents in the Belt and Road Initiative=
[[Machine_Trans_EN_7]]

一带一路背景下人工智能与翻译人才的培养

颜莉莉 Yan Lili, Hunan Normal University, China

=Chapter 8: On Machine Translation Under Lanuguage Intelligence——An Option and Opportunity for Human Translators=
'''论语言智能下的机器翻译——译者的选择与机遇'''

颜静 Yan Jing, Hunan Normal University, China

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=9 谢佳芬（ Machine Translation and Artificial Translation in the Era of Artificial Intelligence）=
[[Machine_Trans_EN_9]]

=10 熊敏(Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts)=
[[Machine_Trans_EN_10]]
===Abstract===
The history of machine translation can be traced to 1940s, undergoing germination, recession, revival and flourish. Nowadays, with the rapid development of information technology, machine translation technology emerged and is gradually becoming mature. Whether manual translation can be replaced by machine translation becomes a widely-disputed topic. So in order to explore the ability of machine translation, I adopts two versions of translation, which are manual translation and machine translation(this paper uses Youdao translation) for different types of texts(according to Peter Newmark's types of text：informative text, expressive text and vocative text). The results are quite different in terms of quality and accuracy. The results show that machine translation is more suitable for informative text for its brevity, while the expressive texts especially literary works and vocative texts are difficult to be translated, because there are too many loaded words and cultural images in expressive text and dependence on the readers. To draw a conclusion, the relationship between machine translation and manual translation should be complementary rather than competitive.

===Key words===
machine translation; manual translation; Newmark's type of texts

===题目===
Research on the English Chinese Translation Ability of Machine Translation for Various Types of Texts

===摘要===
机器翻译的历史可以追溯到上个世纪40年代，经历了萌芽期、萧条期、复兴期和繁荣期四个阶段。如今，随着信息技术的高速发展，机器翻译技术日益成熟，于是机器翻译能不能替代人工翻译这个话题引起了广泛热议。为了探究机器翻译的能力水平是否足以替代人工翻译，本人根据皮特纽马克的文本类型分类理论（信息类文本，表达文本，呼吁文本），选择了相应的译文类型，并且将其机器翻译的版本以及人工翻译的版本进行对比。结果发现，就质量和准确度而言，译文的水平大相径庭。因为其简洁的特性，机器比较适合翻译信息文本。而就表达文本，尤其是文学作品，因其存在文化负载词及相应的文化现象，所以机器翻译这类文本存在难度。而呼唤文本因其目的性以及对读者的依赖性较强，翻译难度较大。由此得知，机器翻译和人工翻译的关系应该是互补的，而不是竞争的。

===关键词===
机器翻译；人工翻译；纽马克文本类型

===1. Introduction===
====1.1.Introduction to machine translation====
Machine translation, also known as computer translation is a technique to translating through machine translator, such as Google translation and Youdao translation. Machine translation is one of the branches of computational linguistics, ranging from computer science, statistics, information science and so on. Machine translation plays an important role in all aspects.
Machine translation can be traced back to 1940s, when British engineer Booth and American engineer Weaver proposed using computer to translate and started to study machines used for translation. And the first machine translating system launched in 1954, used in English and Russian translation. And this means machine translation becomes a reality. However, the arrival of new things always accompanies barriers and setbacks. In the 1960s, reports from ALPAC (Automated Language Processing Advisory Committee) showed studies on machine translation had stagnated for a decade. At that time, due to the high cost of machine, choosing human translators to finish translating works was more economical for most companies. What’s worse, machine had difficulty in understanding semantic and pragmatic meanings. Fortunately, in the 1970s, with the advance and popularity of computer, machine translation was gradually back on track. With the development of science and technology, machine translation has better technological guarantee, such as artificial intelligence and computer technology. In the last decades, from the late 90s till now, machine translation is becoming more and more mature. The initial rule-oriented machine translation has been updated and Corpus-aided machine translation appears. And nowadays, technology in voice recognition has been further developed. This technique is frequently applied in speech translation products. Users only need to speak source language to the online translator and instantly it will speak out the target version. But machine can’t fully provide precise and accurate translation without any grammatical or semantic problems. Machine can understand the literal meaning of texts, but not the meaning in context. For example, there is polysemy in English, which refers to words having multiple meanings. So when translating these words, translators should take contexts into consideration. But machine has troubles in this way. In addition, machine has no feeling or intention. Hence, it is also difficult to convey the feelings from the source language.

====1.2.Process of machine translation====
The process of manual translation is different from that of machine translation. Here is the process of the former. (1) Understand source language. (2) Use target language to organize language. (3) Generate translation. Unlike manual translation, machine translation tends to analyze and code source language first, then look for related codes in corpus, and work out the code that represents target language, generating translation. But they share a common feature, which is that Lexicon, grammatical rules and syntactic structure are taken into consideration. This is one of the biggest challenges for machine translation.

===2.Theorectical framework===
====2.1Newmark’s text typology====
Text typology is a theory from linguistics. It undergoes several phrases. Karl Buhler, a German psychologist and linguist defines communicative functions into expressive, information and vocative. Then Roman Jakobson proposes categorization of texts, which are intralingual translation, interlingual translation and intersemiotic translation. Accordingly, he defines six main functions of language, including the referential function, conative function, emotive function, poetic function, metalingual function and the phatic function. Based on the two theories, Peter Newmark, a translation theorist, summarizes the language function into six parts: the informative function, the vocative function, the expressive function, the phatic function, the aesthetic function, and the metalingual function. Later, he further divided texts into informative type, expressive text and vocative type according to the linguistic functions of various texts.
The core of the informative texts is the truth. It is to convey facts, information, knowledge of certain topics, reality and theories. The language style of the text is objective, logical and standardized. Reports, papers, scientific and technological textbooks are all attributed to informative texts. Translators are required to take format into account for different styles.
The core of the expressive text is the sender’s emotions and attitudes. It is to express sender’s preferences, feelings, views and so on. The language style of it is subjective. Imaginative literature, including fictions, poems and dramas, autobiography and authoritative statements belong to expressive text. It requires translators to be faithful to the source language and maintain the style.
The core of the vocative text is readership. It is to call upon readers to act, think, feel and react in the way intended by the text. So it is reader-oriented. Such texts as advertisement, propaganda and notices are of vocative text. Newmark noted that translators need to consider cultural background of the source language and the semantic and pragmatic effect of target language. If readers can comprehend the meaning at once and do as the text says, then the goal of information communication is achieved.
To draw a conclusion, informative texts focus on the information and facts. Expressive texts center on the mind of addressers, including feelings, prejudices and so on. And vocative texts are oriented on readers and call on them to practice as the texts say.

====2.2Study method====
Manual translations of the three texts are selected from authoritative versions and universally acknowledged. And machine translations of those come from Youdao Translator. And in this thesis I will compare and evaluate the two methods in word diction, sentence structure, word order and redundancy.

===3.Comparison and analysis of machine translation and manual translation ===
====3.1Informative text ====
（1）English into Chinese

①Source language:

Keep the tip of Apple Pencil clean, as dirt and other small particles may cause excessive wear to the tip or damage the screen of i-pad.

Target language:

Machine translation: Apple Pencil笔尖应保持清洁，灰尘等小颗粒可能会导致笔尖过度磨损或损坏ipad屏幕。

Manual translation: 保持Apple Pencil铅笔的笔尖干净，因为灰尘和其他微粒可能会导致笔尖的过度磨损或损坏iPad屏幕。

Analysis: Here is the instruction of Apple Pencil. And the manual translation is the Chinese version on the instruction.Product instruction tends to be professional, since there are many terms for some concepts. Machine can easily identify these terms and provide related words to translate. The machine version is faithful and expressive to the source language. So it is well-qualified and readable for readers to understand the instruction. So we can use machine to translate informative text.

②Source language:

China on Saturday launched a rocket carrying three astronauts-two men and one woman - to the core module of a future space station where they will live and work for six months, the longest orbit for Chinese astronauts.

Target language:

Machine translation: 周六，中国发射了一枚运载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最长的轨道。

Manual translation: 周六，中国发射了一枚搭载三名宇航员(两男一女)的火箭，进入未来空间站的核心舱，他们将在那里生活和工作6个月，这是中国宇航员最漫长的一次轨道飞行。

Analysis: This is a news from Reuters, reporting that China has launched a rocket.The meaning of the two translations is almost the same, except for some word diction. But there are some details dealt with different choice. For example, the last sentence of the machine translation is a bit of obscure and direct. There are some ambiguous words and expressions.

(2)Chinese into English

Source language:湖南省博物馆是湖南省最大的历史艺术类博物馆，占地面积4.9万平方米，总建筑面积为9.1万平方米，是首批国家一级博物馆，中央地方共建的八个国家级重点博物馆之一、全国文化系统先进集体、文化强省建设有突出贡献先进集体。

Target language:
Manual translation: As the largest history and art museum in Hunan province, the Hunan Museum covers an area of 49,000㎡, with the building area reaching 91,000㎡. It is one of the first batch of national first-level museums and one of the first eight national museums co-funded by central and local governments.

Machine translation: Museum in hunan province is one of the largest historical art museum in hunan province, covers an area of 49000 square meters, a total construction area of 91000 square meters, is the first national museum, the central place to build one of the eight national key museum, national cultural system advanced collectives, strong culture began with outstanding contribution of advanced collective.

Analysis: Machine translation is not faithful enough in content. For instance, “首批国家一级博物馆” is translated into “first national museum”, which is not the meaning of the source language. And there are some obvious grammar mistakes in the machine translation. For example, machine translates it into just one sentence but there are multiple predicates in it. So it is not grammatically permissible. What’s more, the sentence structure of machine translation is confusing and the focus is not specific enough.

====3.2Expressive text ====
(1)English into Chinese

Source language:

An individual human existence should be like a river- small at first, narrowly contained within its banks, and rushing passionately past rocks and over waterfalls. Gradually the river grows wider, the banks recede, the waters flow more quietly, and in the end, without any visible breaks, they become merged in the sea, and painlessly lose their individual being.

Target language:

Machine translation: 一个人的存在应该像一条河流——开始很小，被紧紧地夹在两岸中间，然后热情奔放地冲过岩石，飞下瀑布。渐渐地，河面变宽，两岸后退，水流更加平缓，最后，没有任何明显的停顿，它们汇入大海，毫无痛苦地失去了自己的存在。

Manual translation:人生在世，如若河流；河口初始狭窄，河岸虬曲，而后狂涛击石，飞泻成瀑。河道渐趋开阔，峡岸退去，水流潺缓，终了，一马平川，汇于大海，消逝无影。

Analysis: Here is a well-known metaphor in the prose How to Grow Old written by Bertrand Russell. The manual translation is written by Tian Rongchang.This is a philosophical prose with graceful language. Literary translation is a most important and difficult branch of translation. Translator should focus on the literal meaning, culture, writing style and so on. It is a combination of beauty and elegance. Therefore, translators find it in a dilemma of beauty and faithfulness, let alone translating machine. Compared with manual translation, machine translation has difficulty in word choice. It is faithful and expressive, but not elegant enough.

(2)Chinese into English

Source language:没有一个人将小草叫做“大力士”，但是它的力量之大，的确是世界无比。这种力，是一般人看不见的生命力，只要生命存在，这种力就要显现，上面的石块，丝毫不足以阻挡。因为它是一种“长期抗战”的力，有弹性，能屈能伸的力，有韧性，不达目的不止的力。

Target language:

Machine translation: No one calls the little grass "hercules", but its power is truly matchless in the world. This force is invisible life force. As long as there is life, this force will show itself. The stone above is not strong enough to stop it. Because it is a "long-term resistance" of the force, elastic, can bend and extend force, tenacity, not to achieve the purpose of the force.

Manual translation: Though nobody describes the little grass as a “husky”, yet its herculean strength is unrivalled. It is the force of life invisible to naked eye. It will display itself so long as there is life. The rock is utterly helpless before this force- a force that will forever remain militant, a force that is resilient and can take temporary setbacks calmly, a force that is tenacity itself and will never give up until the goal is reached. (by Zhang Peiji)

Analysis:This is the excerpt of a well-known Chinese prose written by Xia Yan. It is written during the war of Resistance Against Japan. So the prose holds symbolic meaning, eulogizing the invisible tenacious vitality so as to encourage Chinese to have confidence in the anti-aggression war. Compared with manual translation, machine translation is much more abstract and confusing, especially for the word diction. For example, “大力士” is translated into “hercules” which is a man of exceptional strength and size in Greek and Roman Mythology, making it difficult to understand if readers of target language have no idea of the allusion. What’s worse, the machine version doesn’t reveal the symbolic meaning of the text, which is the core of this prose.

====3.3Vocative text ====

(1)English into Chinese

①Source language:

iPhone went to film school, so you don’t have to. (Advertisement of iPhone13)

Target language:

Machine translation: iPhone上的是电影学院，所以你不用去。

Manual translation:电影专业课，iPhone同学替你上完了。

Analysis：Here are advertisements of iPhone on Apple official website. There is a personification in the source language. It is used to stress the advancement and proficiency in camera, which is an appealing selling point to potential buyers. Compared with manual translation, machine translation is plain and not eye-catching enough for customers.

②Source language:

5G speed OMGGGGG

Machine language: 5克的速度 OMGGGGG

Manual translation:

iPhone的5G 巨巨巨巨巨5G

Analysis: The “G” in the source language is the unit of speed, standing for generation. However, it is mistaken as a unit of weight, representing gram in the machine translation. So the meaning is not faithful to the source language at all. As for manual translation, it complies with the source in form. Specifically speaking, five “G”s in the former complies with five characters “巨”in the latter. And the pronunciation of the two is similar. There are two layers of meaning for the 5 “G”s. One exclaims the fast speed of 5 generation network and the other new technology. In the manual version, “巨”can be used to show degree, meaning “quite” or “very”.

③Source language:

History, faith and reason show the way, the way of unity. We can see each other not as adversaries but as neighbors. We can treat each other with dignity and respect, we can join forces, stop the shouting and lower the temperature. For without unity, there is no peace, only bitterness and fury."

Target language:

Machine translation: 历史、信仰和理性指明了团结的道路。我们可以把彼此视为邻居，而不是对手。我们可以尊严地对待彼此，我们可以联合起来，停止大喊大叫，降低温度。因为没有团结，就没有和平，只有痛苦和愤怒。

Manual translation:历史、信仰和理性为我们指明道路。那是团结之路。我们可以把彼此视为邻居，而不是对手。我们可以有尊严地相互尊重。我们可以联合起来，停止喊叫，减少愤怒。因为没有团结就没有和平，只有痛苦和愤怒

Analysis: Speech is a way to propagate some activity in public. It is an art to inspire emotion of the audience. The source language is the excerpt of Joe Biden’s inaugural speech. The speech should be inspiring and logic. The machine translation has some misunderstanding. Taking the translation of “lower the temperature” for example, machine only translates its literal meaning, relating to the temperature itself, without considering the context. What’s more, it is less logic than the manual one. Therefore, it adds difficulty to inspire the audience and infect their emotion.

===4.Common mistakes in machine translation ===

====4.1 lexical mistakes ====

Common lexical mistakes include misunderstandings in word category, lexical meaning and emotive and evaluative meaning. Misunderstanding in word category shows in the classification of word in the source language. As for misunderstanding in lexical meaning, machine has difficulty in precisely reflecting the meaning of the original texts, due to different cultural background and different language system. And for misunderstanding in emotive meaning, machine has no intention and emotion like human-beings. Therefore, it’s impossible for it to know writers’ feelings and their writing purposes. So sometimes, it may translate something negative into something positive.

====4.2 grammatical mistakes====

Grammatical analysis plays an important part in translation. Normally speaking, every language has its own unique grammatical rules. So in the process of translation, if translators don’t know the formation rule well, the sentence meaning will be affected. Even though all the lexical meanings are well-known by translators, the lack of consciousness of grammaticality makes it harder to arrange words according to sequential rule. English tends to be hypotactic, while Chinese tends to be paratactic. English sentences are connected through syntactic devices and lexical devices. While Chinese sentences are semantically connected, which means there are limited logical words and connection words in Chinese. So when translating English sentence, we should first analyze its grammaticality and logical structure and then rearrange its sequence. However, online translating machine has troubles in grammatical analysis, which makes its improvement more difficult.

====4.3 other mistakes====

The two mistakes above are the internal ones. Apart from mistakes in linguistic system, there are some mistakes in other aspects, such as cultural background.

===5.Reasons for its common mistakes ===

====5.1 Difference in two linguistic system====

With different history, English and Chinese have different ways of expression. Commonly speaking, English is synthetic language which expresses grammatical meaning through inflection such as tense and Chinese is analytic language which expresses grammatical meaning through word order and function word. In addition, English is more compact with full sentences. Subordinate sentence is one of the most important features in modern English. Chinese, on the other hand, is more diffusive with minor sentences.

====5.2 Difference in thinking patterns and cultural background====

According to Sapir-Whorf’s Hypothesis, our language helps mould our way of thinking and consequently, different languages may probably express their unique ways of understanding the world. For two different speech communities, the greater their structural differentiations are, the more diverse their conceptualization of the world will be. For example, western culture is more direct and eastern culture more euphemistic. What’s more, English culture tends to be individualism, focusing on detail, through which it reflects the whole, while Chinese culture tends to be collective. Different thinking patterns will add difficulty for machine to translate texts.

====5.3 Limitation of computer====

Recently, there are some breakthroughs and innovation in machine translation. However, due to its own limitation, online translation has limitation in some ways. Firstly, compared with machine, human brain is much more complicated, consisting of ten billions of neuron, each of which has different function to affect human’s daily activities and help humans avoid some errors. However, computer can only function according to preset programming has no intention or consciousness. Until now, countless related scholars have invested much time in machine translation. They upload massive language database, which include almost all linguistic rules. But computers still fail to precisely reflect the meaning of source language for many times due to the complexity and flexibility of language. On the other hand, computers can’t take context into consideration. During translation, it is often the case that machine chooses the most-frequently used meaning of one word. So without the correct and exact meaning, readers are easier to feel confused and even misunderstand the meaning of source language.

===6.Conclusion===
From the analysis above, we can draw a conclusion that machine deals with informative text best, followed by non-literary translation of expressive text. What’s more, machine can be a useful tool to get to know the gist and main idea of a specific topic, for the simple sentence structure and numerous terms. And it can improve translating efficiency with high speed. But machine has difficulty in translating literary works, especially proses and poems.

Machine translation has mixed future. From the perspective of commercial, machine translation boasts a bright future. With the process of globalization, the demand for translation is increasing accordingly. On one hand, if we only depend on human translator to deal with translating works, the quality and accuracy of translation can be greatly affected. On the other hand, if machine is used properly to do some basic work, human translators only need to make preparation before translating, progress, polish and other advanced work, contributing to highly-qualified translation and high working efficiency.

However, compared with manual translation, machine translation has a bleak future. It is still impossible for machine to replace interpreter or translator in a short term. With intelligence and initiative, humans are able to learn new knowledge constantly, which machine will never accomplish. Besides, machine is not used to replace translators but to assist them in work. In other words, translators and machine carry out their own duties and they are not incompatible.

To draw a conclusion, although there are certain limitations of machine translation, it can serve as a catalyst for translating works. Therefore, with the rapid development of artificial intelligence and related technology, there are still many opportunities for machine translation.

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=Chapter 11 陈惠妮=Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts=

机器翻译的译前编辑研究——以医学类文摘为例

陈惠妮 Chen Huini, Hunan Normal University

[[Machine_Trans_EN_11]]

===Abstract===
At present, globalization is accelerating and the market demand for language services is rapidly increasing . Machine translation, as an important translation method, can greatly improve translation efficiency due to its low cost and high speed. However, because of the limitations of machine translation and the differences between Chinese and English language, machine translation is not accurate enough. In order to balance translation efficiency and translation quality, a great number of manual revisions in translation are required for the machine translating texts. Medical papers are specialized, special and purposeful, so it requires accurate,qualified and professional translation. However, the quality of translations by machine is inefficient to meet the high-quality requirements of medical papers translation. Therefore, the introduction of pre-editing can greatly improve the efficiency and quality of machine translation.

===Key words===
Pre-editing, Machine translation, Medical texts

===题目===
Study on Pre- editing of Machine Translation - A Case Study of Medical Abstracts

===摘要===
在全球化加速发展的今天，市场对语言服务的需求迅速增加。机器翻译作为一种重要的翻译途径，由于其成本低、速度快，可以大大提高翻译效率。然而，由于机器翻译的局限性以及中英文语言的差异，机器翻译的准确性不高。为了平衡翻译效率和翻译质量，机器翻译文本需要大量的手工修改。
医学论文具有专业性、特殊性和目的性，要求其译文准确、合格、专业。然而，机器翻译的质量较低，无法满足医学论文对翻译的高质量要求。因此，译前编辑的引入可以大大提高机器翻译的效率和质量。

===关键词===
译前编辑；机器翻译；医学文本

===1. Introduction===
===1.1 Definition of Machine Translation===
As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.

As Cronin(2013) revealed: "Translation is undergoing a revolutionary upheaval. The influence of digital technology and the Internet on translation is continuous, extensive and profound. From the popularity of automatic online translation applications, translation revolution is everywhere (Cronin,2013) However,the concept of machine translation was firstly proposed in the 1930s. Since 1940s, the machine translation technology has been evolving from rule-based machine translation (RBMT) to statistical machine translation (SMT), and to neural machine translation (NMT). Machine translation refers to the automatic translation of source language into target language by using a computer system. That is, machine translation refers to the automatic translation of text from one language into another natural language by computer software or other online translation webs. Machine translation is also defined as the process of “using a computer system to automatically translate text or speech from one natural language to another” according to the definition by ISO (Cui 2014:68-73).O 'Brien (2002) defines it as "the behavior of modifying errors in machine translation to ensure that the target translation meets certain quality requirements". On the basic level, machine translation performs mechanical substitution of words in one language for words in another language, but that rarely produces a good translation, therefore, recognition of the whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalents in another language, and many words have more than one meaning. A huge demand for translation is greatly needed in today’s global world, which creates new opportunities for the development of machine translation, attracts more and more attention and becomes one of the current research focuses.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:34, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.2 Definition of Pre-editing===
Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)

Pre-editing means to adjust and modify the source language to make it fit more with the characteristics of the machine translation software before putting the source language before the into machine translation, so as to improve the quality of the translation machine translation (Wei Changhong 2008:93-94). Pre-editing is to modify the original text before putting it into machine translation software, in order to improve the recognition rate of machine translation, optimize the output quality of translated text and reduce the workload of post-editing. Because pre-translation editing only needs to be modified in one language, the operation is simpler than post-translation editing, which can realize the double improvement of quality and efficiency. A good pre-editing translation can help machine translation more smoothly, thus improving the machine readability and quality of the output translation. Pre-editing is mostly applied in the following situations: one is when the original text is of poor quality and the machine is difficult to recognize the meaning of the sentence, such as user generated content with poor readability and translatability (Gerlach et al 2003:45-53); Documents that need to be published in multiple languages; Next is when the original text contains a lot of jargon; The last is the original text has a corresponding translation memory bank. If the original text is edited, it can better match the content of the translation memory bank. Pre-editing is a process of identifying problems. It requires to pre-edit the source texts before putting it into machine translation according to the requirements, listing the expressions or sentences that may have trouble in machine translation and then pre-edit it by human. The purpose is to enable the computer to translate better, improve the translatability of machine translation. (Slype G V & Guinet J F & Seitz F 1984:115)
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:36, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.3 Machine Translation Mode===
According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

According to the different knowledge acquisition methods, machine translation modes can be classified as follows: one is rule-based machine translation, which is based on bilingual dictionaries and a library of language rules for each language. The quality of translation depends on whether the source language conforms to the existing rules, but the inexhaustible rules are the hinders of this model. The second mode is machine translation based on statistics. This translation model relies on the principles of mathematics and statistics to find various existing translations corresponding to the translation tasks through the employment of corpus, analyzing the frequency of their occurrence and selecting the translation with the highest frequency for output. The disadvantage of this translation model is that it ignores the flexibility of language and the importance of context. The last one is neural network language model. This model is different from previous translation models in that it uses end-to-end neural network to realize automatic translation between natural languages. At present, the quality of its translation is much higher than that of the previous translation models.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.4 Source of Study Abstracts===
The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

The core medical journals from domestic are selected in order to make the paper more representative and authoritative, such as National Medical Journal of China, Journal of Peking University (Health Science), and Journal of Third Military Medical University. All of them include basic medical science, biomedical technology, laboratory medical science and other fields. In this way, the pre-editing approaches included are applicable enough to machine translation of medical abstracts.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===1.5 Selection of Translation Software===
Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

Generally, machine translation software includes Google Translation, Youdao Translator and Niu Translation, which has their own special use in translation. Take Google as an example, it is more like neurons in human brain, enabling to learn and collect information to establish connections with its neural machine translator’s neurons. However, it also causes many errors because of the lack of enough information. In this paper, contrastive analysis will be carried on by using Google translation. On the one hand, being a pioneer in the translation of NET, it is inevitably to sue Google as the translation software to translate medical texts in this paper. Comparing the program called “Google brain”, other NMT of translation software are relatively disadvantages. On the other hand, the Google translation enjoys the largest users in the world, with its downloads of more than one billion. The output quality of Google translation is more correct and complete than other machine translation software. With years of development and improvement, Google Translation has been greatly promoted. In this paper, Chinese medical abstract will be automatically translated by Google translation, and then the translation output will be compared with the translation by human and the publication of English abstracts. The main purpose is to prove that the improvement and promotion of quality and accuracy in the medical abstracts will be obtained through the pre-editing approaches.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.Language Characteristics and Error Division===
Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

Since Chinese and English are two different languages, it is quite neccessary to identify their own characteristics so as to better analyze and understand the two languages. Tytler (1978: 118-119) argued in his Essay on the Principles of Translation that there are three principles of translation that in all the translation should give readers the same feelings as the source text, except for complete transcript of ideas. There actually also exit some mistakes of these two languages. So the following will make some clarrifications of these two languages to ensure more accurate translation.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.1 Language Characteristics of Medical Abstracts===
Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.

Chinese and English belong to different language systems, so there are differences in their language structure and the way users think of the languages. When using machine translation from Chinese to English, due to the unequal language levels, there will be many mistakes in the translation process, especially for ESP texts, such as medical papers.Here, these differences mainly refer to the linguistic characteristics of medical abstracts. In medical abstracts, it usually includes structured and unstructured abstracts. Although in different forms, they both describe the purpose, methods and conclusions of the research.

In the method section of medial abstract, several Chinese sentences can be connected with commas, but each sentence may convey different information. In contrast, English sentences contain a great deal of information, but in order to ensure clarity, some modifiers need to be isolated and then reconstructed. However, in Chinese-English machine translation, a lot of information is put into the sentence because the machine segments the sentence on the basis of the full comma.

In addition, subjectless sentence is used in the objective and method parts of Chinese medical abstracts. The subjectless sentence means the sentence without or free from subject and is usually employed in two contexts. The first is "needless to say". In Chinese sentences, it is common to omit the subject of the sentence. Chinese sentences can convey meanings by using incomplete sentence structures, so Chinese speakers can understand the meanings of the sentences even though the sentence subject is omitted. The second is "emphasis of action". In this context, subjectless sentences are used to describe behaviors, especially in the study of traditional Chinese medicine abstracts. Comparatively speaking, it should be avoided in English medical abstracts. Abstract sentences are more subjective when describing the learning process, while the essential requirement of English medical abstract is objectivity. From this point, sentences without subject should be avoided in English medical abstracts. Another feature is voice. Few words with passive meanings appear in Chinese abstracts. English sentences are more favoured in using passive voice. When translating from Chinese to English, passive voice should be used to make the contents objective, which is also the basic requirement of medical papers.

These are the linguistic features of Chinese medical abstracts. There are great differences in sentence structure and expression between Chinese and English medical abstracts. These differences may reduce the accuracy of machine translation, so it is necessary to introduce pre-editing to edit the source text to ensure that the source text can be accurately recognized by the machine and fully translated into English.
--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===2.2 Error Division of Machine Translation in Translating Abstracts of Medical Papers from Chinese to English===
In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

In this paper, errors in machine translation are listed out after analyzing. Some are due to the principles, such as statistical-based MT and NMT, employed by machine translation. Based on the original errors, they can be studied from two levels. One is from the macro-level, referring to mistakes caused by objective factors. These are not human factors, but the disadvantage of machine translation and the limitations of language. The limitations of machine translation are derived from the principles and models adopted and manifests itself as a reliance on reference sources. In this case, semantic ambiguity and textual incoherence may occur in the absence of reference sources.

However, for ESP texts such as medical papers, the requirements for terms and sentence patterns are far beyond the existing corpora. For unfamiliar texts (that is, the corresponding texts cannot be found in the corpora). The quality of output translation will be relatively low, which is determined by the principles of machine translation. As mentioned above, machine translation has evolved over the past few decades from rules-based to corp-based statistics to NMT. However, there still exist some limitations in machine translation.

Mistakes on micro-level are mainly caused by the variations and differences of linguistic structure between Chinese and English. Chinese is an implicit language, while English is an explicit one (Lian, 2010) To put it in another way, Chinese expression does not depend on language structures, while English does the opposite. This may result in mismatches between the original and machine translated sentences. This kind of error is mainly divided into two types: component fragment and component missing. For a medical paper, such errors are very serious. As a kind of ESP discourse, medical paper has the characteristics of fixed, objective and accurate language structure. In order to reproduce the characteristics of medical abstracts in translation, it is necessary to avoid errors at the level of words and sentences and pay attention to logic and consistency.

Lexical errors here refer to the inconsistency of fixed expressions in the translation of terms. Although these terms are machine translation based on the corpus, the corpus may not be perfect for ESP texts such as medical papers. Therefore, fixed expressions are not used in term translation. This is also the most common mistake in machine translation (the term here includes but is not limited to nouns). For ESP texts, medical text in particular, the fixed expressions and the accuracy of terms are of great importance.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.Approaches Proposed for Pre-editing ===
Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.
Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".
The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

Generally speaking, there is a close relationship between pre-editing and post-editing, both of which aim to convey information and ensure high or publishable translation quality. Proper pre-editing can improve the quality of machine translation in terms of adequacy and consistency.

Complexity of natural language and people use language arbitrarily, bringing many difficulties to Chinese-English machine translation, Hu Qingping (2005:24) has proposed "the research of translation software and the development of the controlled language are the two directions to improve the quality of machine translation : the former aims at the difficulty in the natural language processing, the latter overcomes the arbitrariness of natural language". Feng Quangong and Gao Lin (2017: 63-68) put forward: "The writing principles of controlled language can be applied to pre-editing of machine translation. Pre-editing based on controlled language can effectively reduce the complexity and ambiguity of source text, improve the identifiability of machine translation (the translatability of source text itself), and thus reduce (fully) the workload of post-editing".

The central task of pre-editing is to transform human-friendly content into machine-friendly content, so words and sentences need to be repositioned or even changed. Based on the analysis of the language characteristics of Chinese and English, the Chinese ideographic group should be split before the Chinese source text is input into the machine software to translate so that the sentence structure is complete which can be easily recognized by the machine translation software.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufefng

===3.1 Extraction and Replacement of Terms in the Source Text===
As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.
Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

As a branch of applied English, medical English is the product of the combination of English language knowledge and medical knowledge. The terms in medical papers have the characteristics of fixed and complex language structure. Although Google Translation is based on a corpus, the language structure is not fixed due to the limited size of the corpus. Therefore, the following two steps should be followed before machine translation. The first is to extract terms and create a glossary, and then replace the Chinese terms in the source text with the corresponding English expressions in the glossary. Of course, the terms of extraction should be searched and verified according to the actual situation. All of these words are verified before they can be replaced. This method can not only ensure the accuracy of term translation, but also maintain the consistency of expression, especially when dealing with long texts.

Example1
Source abstract: 口腔白斑病癌变相关缺氧应答基因和微小RNA的芯片及表达验证。
Google translation: Microarray detection/Chip detection and expression verification of hypoxia response genes and microRNAs related to oral leukoplakia canceration.
Published translation:Transcriptome array screening and verification of oral leukoplakia carcinogenesis-related hypoxia-responsive gene and microRNA.
Analysis: The expression “ Affymetrix GeneChip” empolyed in this thesis is a human transcription array for transcriptome array. In the source abstract, “芯片检测“ can be meant “screening” but not detection, so the proper and appropriate translation of these expression should be “transcription array screening”, but the Google translates it into “microarry detection of chip detection”. Therefore, term extraction is essential and inevitable before putting the source abstracts into the machine translation software.
After pre-editing source abstracts: 对 oral leukoplakia carcinogenesis 相关 hypoxia-responsive gene 和微小RNA进行 transcriptome array screening 及表达验证。
After pre-editing translation: Transcriptome array screening and expression- verification of hypoxia-responsive genes and microRNAs related to oral leukoplakia carcinogenesis.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.2 Explication of Subordination===
As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.
Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

As mentioned above, the subordination of Chinese sentences is judged by certain specific words in machine translation . Chinese is a paratactic language, and sentences are often connected by internal logical relationships; while English depends on sentence structure, so sentences are often closely linked by various language forms. In order to improve the accuracy of machine translation, we can adjust the sentence structure and adjust the position of adjectives and their modifiers.

Example 2
Source abstracts:回顾性分析南京医科大学附属儿童医院中重度HIE患儿49例及同期就诊的无神经系统症状体征的足月新生儿为对照组31例的头颅磁共振成像（MRI）资料。
Google translation: A retrospective analysis that the brain magnetic resonance imaging (MRI) data of 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University and full-term neonates with no neurological symptoms and signs during the same period were included in the control group.
Published translation: A total of 49 children with moderate to severe HIE admitted to the children’s Hospital Affiliated to Nanjing Medical University were retrospectively analyzed. Cranial magnetic resonance imaging (MRI) date of 31 full-term neonates without neurological symptoms and signs who visited the hospital during the same period were recruited as the control group.

Analysis: As the above example shows that “中重度HIE患儿” and “足月新生儿” in the source abstracts are from the Children’s Hospital Affiliated Nanjing Medical University. The Google translation shows that 49 children with moderate to severe HIE in the Children's Hospital of Nanjing Medical University. There is an error due to the misuse of subordination. There are some advice in order to solve the problem. That is, first to segment the sentence and then reconstruct the sentence. For instance, the Chinese expression “南京医科大学附属儿童医院” carries many modifiers, which requires to cut the modifiers and reconstruct the sentence.

Therefore, the Chinese expression “南京医科大学附属儿童医院’can be divided into abstractions, leaving two sentences instead of one long sentence with modifiers..
After pre-editing source abstracts: 对49例中重度HIE患儿以及31例无神经系统症状体征的足月新生儿的MRI资料进行回顾性分析。这些患者收治于南京医科大学儿童附属医院。
After pre-editing translation: The MRI data of 49 children with moderate to severe HIE and 31 full-term newborns without neurological symptoms and signs were retrospectively analyzed. These patients were admitted to the Children’s Hospital of Nanjing Medical University.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.3 Explication of Subject through Voice Changing===
The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.
Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.
Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

The extensive use of subjectless sentences are quite common in the Chinese abstracts, while English prefers to employ passive voice in the sentences so as to make them object and accurate. In order to take the characteristics of English sentences into great and careful consideration, the sentences written in passive voice in particular, it will be helpful for machine translation to find out the subject and reconstruct a sentence in passive voice (Wang Yan: 2008). The first is to discover the “doee” in a sentence and then is to reconstruct the sentence structure and put the “doee” before the verb. The last is to explicate the passive relation between the noun and the verb.

Example 3
Source abstract: 回顾性分析2018年1月至2020年12月解放军总医院第七医学中心收治的500例老年髋部骨折患者的资料。
Google translation: A retrospective analysis of the data of 500 elderly patients with hip fractures admitted to the Seventh Medical Center of the PLA General Hospital from January 2018 to December 2020.
Published translation: From January 2018 to December 2020, the data of 500 elderly patients with hip fracture treated in the Seventh Medical Center of PLA General Hospital were analyzed retrospectively.

Analysis: The above example indicates that the “回顾性分析”in the Google Translate is a noun phrase, but the source abstracts actually describes an action or a behavior. The reason for such a mistake is that the machine can’t recognize the Chinese subjetless sentences. To find the subject of the sentence, the source abstracts can be revised and adjusted. Finding the “doee” is the first step, which refers to “500例老年髋部骨折患者的资料”in the source abstracts. And next is to put it in front of the verb, that is to place it in the beginning of the sentence. Last but not least, the passive voice should be explicated in the sentence.
After pre-editing source abstract: 500例老年髋部骨折患者的资料被回顾性分析，他们在2018年1月之2020年12月期间收治于解放军总医院第七医学中心。
After pre-editing translation: The data of 500 elderly hip fracture patients were retrospectively analyzed. They were admitted to the Seventh Medical Center of the PLA General Hospital between January 2018 and December 2020.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.4 Relocation of Modifiers===
Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

Modifiers, including noun, adverbial and attributive are constantly employed in the Chinese medical papers in order to add information to subject and object in the sentence. By doing this, complicated sentences can be structured, thus causing obstacles to machine translation for recognizing this complex sentence structures when translating Chinese-English sentences. To make the machine translation successfully recognize the sentence structure, simplifying the sentence structure is quite necessary. The key is to moving the location of the modifiers and thus making the modifiers an independent sentence. In other words, the modifiers ought to be put before or behind the main part of the sentence to satisfy the common use of English.
Usually, the modifiers in Chinese sentence can only be placed in front of the core word, while in English, modifiers are very flexible. It is all right to place the modifiers in front of or behind the major part of the sentences with adjective or a connective noun.

Example 4
Source abstracts: 利用DNA重组技术以pET-28a表达系统在E.coli BL21(DE3) 中重组表达Hepl。
Google Translation: Hepl is recombined in E.coli BL21 (DE3) using DNA recombination technology with pET-28a expression system.
Published translation: The recombinant Hcpl protein was expressed by using DNA recombination technology through pET-28a expression system in E. coli BL21 (De3).
Analysis: The Chinese medical text includes two modifiers, “利用DNA”and “以pET-28a)表达系统”. These two modifiers will be translated by machine, which catches more attention to the two constituents. From the Google translation above, one failure is obvious that it misplaces the location of the two modifiers and presents it in not accurate form. To make it translate correctly by machine translation, dividing the sentences is very important so that the source abstracts can be correctly recognized by machine translation.

After pre-editing source abstract: 利用DNA重组技术，Hcp1重组表达在E.coli BL21 (DE3)中，通过pET-28a表达系统在E. coli BL21 (DE3)中。
Google translation: Using DNA recombination technology, Hcp1 recombination is expressed in E.coli BL21 (DE3), via pET-28a expression system in E. coli BL21 (DE3).
The second is the independence of modifiers, that is, modifiers can also be reconstructed into clauses to modify core words. Compared with English, There is no subordinate clause in Chinese, so redundant Chinese modifiers need to be reconstructed into subordinate clauses in Chinese-English translation to meet the characteristics of English. English, especially sentences with multiple modifiers. Otherwise, sentence structure may be confused, such as scattered modifiers of core words. To avoid this mistake, it is necessary to separate the modifier from the main part of the sentence. These modifiers should be reconstituted into clauses. Also, keep your sentences simple and easy to understand.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===3.5 Proper Omission and Deletion of Category Words===
Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

Category words are commonly used in Chinese. Category words complement the meaning of words, including problems, positions, situations and jobs. Adding this supplementary word is more in line with Chinese custom. In many cases, it has no real meaning, so it can be omitted in translation. In Chinese, category words are frequently used. However, it is rarely used in English, which is one of the differences between Chinese and English. There are many kinds of category words. Considering objectivity and the fixed structure of language, redundant category words should be deleted in Chinese-English translation. In the general, the most commonly used category of words in the Chinese medical abstracts are "process", "behavior", and "situation". These categories of words hinder the language conversion of Chinese and English, resulting in redundancy.

Example 5
Source abstract: 探讨口腔白斑病癌变进程中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia response genes and associated microRNAs in the process of oral leukoplakia cancer was discussed.
Published translation: To study the hypoxia response gene and microRNA (miRNA)expression profiles in the pathogenesis and progression of oral leukoplakia (OLK).
Analysis: As the above example shows, the Chinese words “进程” belongs to a category word. However, the Chinese expression “癌变”contains the process, so the “进程” expression can be deleted before placing it into the machine translation, because the meaning of it has been overlapping between the expression “癌变”. Therefore, its place can be replaced with preposition “during”.

After pre-editing source abstract: 探讨口腔白斑病癌变中的缺氧应答基因及相关微小RNA (miRNA) 的表达。
Google translation: The expression of hypoxia responsive genes and miRNA in oral leukoplakia cancer was investigated.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===Conclusion===
After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

After years of development, machine translation has made great progress. The accuracy of machine translation has been greatly improved in both text recognition and sentence pattern conversion. However, machine translation has its own limitations. In other words, it needs to rely on the parallel corpus as a reference source for improving its accuracy. ESP text, in particular, is harder to get the high quality by machine translation.

As one of the research papers, the characteristics of medical abstracts are fixed language structures, objectivity and accuracy (Qin Yi 2004:421-423). Therefore, medical translation must be accurate, object and understandable to follow the specific demands of the medical paper. Being an important field in the human society, medical paper translation is on a great demand, which means that it needs a huge demand for human labor. However, with the machine translation promoting, it will be more efficient to translate medical papers combining the effort by human and machine. The improvement and development of machine translation requires the joint efforts of computer science, information science, statistics, linguistics and other academic circles to achieve more mature human-computer mutual assistance translation (Li Yafei, Zhang Ruihua 2019:38-45).

However, errors can occur during the process of machine translation of Chinese- English, because of the differences of the Chinese and English and the processing of the machine. Errors from the perspective of linguistic or grammar can affect the machine translation a lot. After division and recognition of errors, some pre-editing approaches are put forward to help the machine translation more accurate and readable, that are, extraction and replacement of terms in the source text, relocation of modifiers, explication of subordination, proper omission, deletion of category words and explication of subject through voice changing.

The paper mainly focuses on the pre-editing machine translation by using medical papers as a case study. The errors of machine translation occurring in the translation of medical abstracts and pre-editing approaches for machine translation. The quality of machine translation of medical papers is greatly improved after employing the pre-editing methods. However, machine translation is not as flexible and accurate as human brain, so it is of importance to combine pre-editing and post-editing approaches with machine translation in order to produce more accurate, more object machine translation of medical papers.

--[[User:Cai Zhufeng|Cai Zhufeng]] ([[User talk:Cai Zhufeng|talk]]) 13:48, 13 December 2021 (UTC)correted by Cai Zhufeng

===References===

Cui Qiliang崔启亮(2014).论机器翻译的译后编辑[J] ''On Post-Editing of Machine Translatio''. 中国翻译 Chinese Translators Journal, 035(006):68-73

Feng Quangong, Gao Lin冯全功,高琳 (2017). 基于受控语言的译前编辑对机器翻译的影响[J] ''Influence of Pre-editing Based on Controlled Language on Machine Translation''. 当代外语研究Contemporary Foreign Language Research,(2): 63-68+87+110.

GERLACH J, et al ( 2013). ''Combining Pre-editing and Post-editing to Improve SMT of User-generated Content''[M]// Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice. 45-53

Hu Qingping胡清平(2005). 机器翻译中的受控语言[J] ''Controlled Language in Machine Translation''. 中国科技翻译 Chinese Science and Technology Translation, (03): 24-27.

Lian Shuneng连淑能 (2010). 英汉对比研究增订本[M]''An Updated Version of English-Chinese Contrastive Studies'' . 北京:高等教育出版社Beijing: Higher Education Publishing House. 35-36.

Li Yafei, Zhang Ruihua黎亚飞,张瑞华 (2019). 机器翻译发展与现状[J]''The Development and Current Situation of Machine Translation''. 中国轻工教育 China Light Industry Education, (5):38-45.

Qin Yi秦毅(2004),从翻译基本标准议医学英语的翻译[J] ''On the Translation of Medical English from the Basic Standard of Translation''. 遵义医学院学报 Journal of Zunyi Medical College,27 (4): 421-423.

Slype G V & Guinet J F & Seitz F (1984). ''Better Translation for Better Communication'' [M] . Oxford: Pergamon Press Ltd (U.K.). 90-93

O'Brien S (2002). Teaching Post-editing: A Proposal for Course Con-tent [EB/OL]. http://mt-archive. Info/EAMT-2002-0brien. Pdf.

Tytler, A. F. (1978). ''Essay On The Principles of Translation''[M]. Amsterdam: JohnBenjamins Publishing. 118-119

Wang Yan王燕 (2008). 医学英语翻译与写作教程[M] ''Medical English Translation and Writing Course''. 重庆:重庆大学出版社 Chongqing: Chongqing University Press. 60-61

=12 蔡珠凤=(The Mistranslation of C-J Machine Translation of Political Statements)=

机器翻译中政治发言中译日的误译

蔡珠凤 Cai Zhufeng, Hunan Normal University

[[Machine_Trans_EN_12]]
===Abstract===
Language is the main way of communication between people. With the continuous development of globalization, the scale of cross-border exchanges is also expanding. However, due to cultural differences and diversity, the languages of different countries and regions are very different, which seriously hinders people's communication. The demand for efficient and convenient translation tools is increasing. At the same time, with the development of network technology and artificial intelligence, recognition technology based on deep learning is more and more widely used in English, Japanese and other fields.

===Key words===
machine translation; political statements; mistranslation of C-J machine translation
===题目===
The Mistranslation of C-J Machine Translation of Political Statements
===摘要===
语言是人与人之间交流的主要方式。随着全球化的不断发展，跨境交流的规模也在不断扩大。然而，由于文化的差异和多样性，不同国家和地区的语言差异很大，这严重阻碍了人们的交流。对高效便捷的翻译工具的需求正在增加。同时，随着网络技术和人工智能的发展，基于深度学习的识别技术在英语、日语等领域的应用越来越广泛。

===关键词===
机器翻译；政治发言；政治发言中译日的误译
===1. Introduction===
===Introduction to machine translation===
Machine translation, also known as automatic translation, is a process of using computers to convert one natural language (source language) into another natural language (target language). It is a branch of computational linguistics, one of the ultimate goals of artificial intelligence, and has important scientific research value.At the same time, machine translation has important practical value. With the rapid development of economic globalization and the Internet, machine translation technology plays a more and more important role in promoting political, economic and cultural exchanges.The development of machine translation technology has been closely accompanied by the development of computer technology, information theory, linguistics and other disciplines. From the early dictionary matching, to the rule translation of dictionaries combined with linguistic expert knowledge, and then to the statistical machine translation based on corpus, with the improvement of computer computing power and the explosive growth of multilingual information, machine translation technology gradually stepped out of the ivory tower and began to provide real-time and convenient translation services for general users.（Zhang 2019:5-6)

=== C-J machine translation software===
Today's online machine translation software includes Baidu translation, Tencent translation, Google translation, Youdao translation, Bing translation and so on. Google was the first company to launch the machine translation system, and Baidu was the first company to import the machine translation system in China. In addition, Tencent and Youdao have attracted much attention.Machine translation is the process of using computers to convert one natural language into another. It usually refers to sentence and full-text translation between natural languages. In order to continuously improve the translation quality, R & D personnel have added artificial intelligence technologies such as speech recognition, image processing and deep neural network to machine translation on the basis of traditional machine translation based on rules, statistics and examples.With the increase of using machine translation, the joint cooperation between manual translation and machine translation will also increase significantly in the future. What criteria should be used to evaluate the quality of machine translation? In the evolving field of machine translation, there is an urgent need to clarify the unsolvable questions and solved problems.(Lv 1996:3)

===The history of machine translation===
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, the French scientist G.B. alchuni put forward the idea of using machines for translation. In 1933, Soviet inventor П.П. Trojansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; However, due to the low technical level in the 1930s, his translation machine was not made. In 1946, the first modern electronic computer ENIAC was born. Shortly after that, W. weaver, an American scientist and A. D. booth, a British engineer, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947 when discussing the application scope of electronic computer. In 1949, W. Weaver published the translation memorandum, which formally put forward the idea of machine translation. After 60 years of ups and downs, machine translation has experienced a tortuous and long development path. The academic community generally divides it into the following four stages:

Pioneering period（1947-1964）

In 1954, with the cooperation of IBM, Georgetown University completed the English Russian machine translation experiment with ibm-701 computer for the first time, showing the feasibility of machine translation to the public and the scientific community, thus opening the prelude to the study of machine translation.
It is not too late for China to start this research. As early as 1956, the state included this research in the national scientific work development plan. The topic name is "machine translation, the construction of natural language translation rules and the mathematical theory of natural language". In 1957, the Institute of language and the Institute of computing technology of the Chinese Academy of Sciences cooperated in the Russian Chinese machine translation experiment, translating 9 different types of more complex sentences.From the 1950s to the first half of the 1960s, machine translation research has been on the rise. The United States and the former Soviet Union, two superpowers, have provided a lot of financial support for machine translation projects for military, political and economic purposes, while European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs, and machine translation has become an upsurge for a time. In this period, although machine translation is just in the pioneering stage, it has entered an optimistic period of prosperity.

Frustrated period（1964-1975）

In 1964, in order to evaluate the research progress of machine translation, the American Academy of Sciences established the automatic language processing Advisory Committee (Alpac Committee) and began a two-year comprehensive investigation, analysis and test.In November 1966, the committee published a report entitled "language and machine" (Alpac report for short), which comprehensively denied the feasibility of machine translation and suggested stopping the financial support for machine translation projects. The publication of this report has dealt a blow to the booming machine translation, and the research of machine translation has fallen into a standstill. Coincidentally, during this period, China broke out the "ten-year Cultural Revolution", and basically these studies also stagnated. Machine translation has entered a depression.

convalescence（1975-1989）

Since the 1970s, with the development of science and technology and the increasingly frequent exchange of scientific and technological information among countries, the language barriers between countries have become more serious. The traditional manual operation mode has been far from meeting the needs, and there is an urgent need for computers to engage in translation. At the same time, the development of computer science and linguistics, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, have promoted the recovery of machine translation research from the technical level. Machine translation projects have begun to develop again, and various practical and experimental systems have been launched successively, such as weinder system Eurpotra multilingual translation system, taum-meteo system, etc.However, after the end of the "ten-year holocaust", China has perked up again, and machine translation research has been put on the agenda again. The "784" project has paid enough attention to machine translation research. After the mid-1980s, the development of machine translation research in China has further accelerated. Firstly, two English Chinese machine translation systems, ky-1 and MT / ec863, have been successfully developed, indicating that China has made great progress in machine translation technology.(Chen 2016:5)

New period(1990 present)

With the universal application of the Internet, the acceleration of the process of world economic integration and the increasingly frequent exchanges in the international community, the traditional way of manual operation is far from meeting the rapidly growing needs of translation. People's demand for machine translation has increased unprecedentedly, and machine translation has ushered in a new development opportunity. International conferences on machine translation research have been held frequently, and China has made unprecedented achievements. A series of machine translation software have been launched, such as "Yixing", "Yaxin", "Tongyi", "Huajian", etc. Driven by the market demand, the commercial machine translation system has entered the practical stage, entered the market and came to the users.Since the new century, with the emergence and popularization of the Internet, the amount of data has increased sharply, and statistical methods have been fully applied. Internet companies have set up machine translation research groups and developed machine translation systems based on Internet big data, so as to make machine translation really practical, such as "Baidu translation", "Google translation", etc. In recent years, with the progress of in-depth learning, machine translation technology has further developed, which has promoted the rapid improvement of translation quality, and the translation in oral and other fields is more authentic and fluent.(Liu 2014:6)

===The problem of machine translation at present===
Error is inevitable
Many people have misunderstandings about machine translation. They think that machine translation has great deviation and can't help people solve any problems. In fact, the error is inevitable. The reason is that machine translation uses linguistic principles. The machine automatically recognizes grammar, calls the stored thesaurus and automatically performs corresponding translation. However, errors are inevitable due to changes or irregularities in grammar, morphology and syntax, such as sentences with adverbials after "give me a reason to kill you first" in Dahua journey to the West. After all, a machine is a machine. No one has special feelings for language. How can it feel the lasting charm of "the tenderness of lowering its head, like the shame of a water lotus? After all, the meaning of Chinese is very different due to the changes of morphology, grammar and syntax and the change of context. Even many Chinese people are zhanger monks - they can't touch their heads, let alone machines.(Liu 2014：3）

Bottleneck
In fact, no matter which method, the biggest factor affecting the development of machine translation lies in the quality of translation. Judging from the achievements, the quality of machine translation is still far from the ultimate goal.
Chinese mathematician and linguist Zhou Haizhong once pointed out in his paper "fifty years of machine translation": to improve the quality of machine translation, the first thing to solve is the problem of language itself rather than programming; It is certainly impossible to improve the quality of machine translation by relying on several programs alone. At the same time, he also pointed out that it is impossible for machine translation to achieve the degree of "faithfulness, expressiveness and elegance" when human beings have not yet understood how the brain performs fuzzy recognition and logical judgment of language. This view may reveal the bottleneck restricting the quality of translation.
It is worth mentioning that American inventor and futurist ray cozwell predicted in an interview with Huffington Post that the quality of machine translation will reach the level of human translation by 2029. There are still many disputes about this thesis in the academic circles.（Cui 2019：4）

===2.Mistranslation of Chinese Japanese machine translation===
===2.1Vocabulary mistranslation in Chinese Japanese machine translation===
===2.1.1Mistranslation of proper nouns===
In political materials, there are often political dignitaries' names, place names or a large number of proper nouns in the political field. The morphemes of such words are definite and inseparable. Mistranslation will make the source language lose its specific meaning.

Japanese translation into Chinese Chinese translation into Japanese

original text translation by Youdao reference translation original text translation by Youdao reference translation

朱鎔基朱基朱镕基栗战书栗戰史書栗戰書

労安劳安劳安李克强李克強李克強

筑紫哲也筑紫哲也筑紫哲也习近平習近平習近平

山口百惠山口百惠山口百惠韩正韓中韓正

田中角栄田中角荣田中角荣王沪宁王上海氏王滬寧

東条英機东条英社东条英机汪洋汪洋汪洋

毛沢东毛泽东毛泽东赵乐际趙樂南趙樂際

トウ・ショウヘイ　　　大酱邓小平江泽民江沢民江沢民

周恩来周恩来周恩来

クリントン克林顿克林顿

The above table counts 18 special names in the two texts, and 7 machine translation errors. In terms of mistranslation, there are not only "战书" but also "戰史" and "史書" in Chinese. "沪" is the abbreviation of Shanghai. In other words, since "战书" and "沪" are originally common nouns, this disrupts the choice of target language in machine translation. Except Katakana interference (except for トウシゃウヘイ, most of the mistranslations appear in the new Standing Committee. It can be seen that the machine translation system does not update the thesaurus in time. Different from other words, people's names have particularity. Especially as members of the Standing Committee of the Political Bureau of the CPC Central Committee, the translation of their names is officially unified. In this regard, public figures such as political dignitaries, stars, famous hosts and important. In addition, the machine also translates Japanese surnames such as "タ二モト" (谷本), "アンドウ" (安藤) into "塔尼莫特" and "龙胆". It can be found that the language feature that Japanese will be written together with Chinese characters and Hiragana also directly affects the translation quality of Japanese Chinese machine translation. Japanese people often use Katakana pronunciation. For example, when Japanese people talk with Premier Zhu, they often use "二ーハウ" (Hello). However, the machine only recognizes the two pseudonyms "二" and "ハ" and transliterates them into "尼哈" , ignoring the long sound after "二" and "ハ".(Guan 2018:10-12)

original text Translation by Youdao reference translation

日美安全体制日米の安全体制日米安保体制

中国共产党第十九次全国代表大会中国共産党第19回全国代表大会中国共産党第19回全国代表大会（第19回党大会）

十八大十八大第18回党大会中国特色社会主义

中国特色社会主義中国の特色ある社会主義第18回党大会

中国共产党中央委员会中国共産党中央委員会中国共産党中央委員会

中国共産党中央委員会十八届中共中央政治局常委第18代中国共產党中央政治局常務委員第18期中共中央政治局常務委員

十八届中共中央政治局委员 18期の中国共產党中央政治局委員第18期中共中央政治局委員

十九届中共中央政治局常委十九回中国共產党中央政治局常務委員第19期中央政治局常務委員

中共十九届一中全会中国共產党第十九回一中央委員会第19期中央委員会第1回全体会議

The above table is a comparison of the original and translated versions of some proper nouns. As shown in the table, the mistranslation problems are mainly reflected in the mismatch of numerals + quantifiers, the wrong addition of case auxiliary word "の", the lack of connectors, the Mistranslation of abbreviations, dead translation, and the writing errors of Chinese characters. The following is a specific analysis one by one.

"十八届中共中央政治局常委", "十八届中共中央政治局委员", "十九届中共中央政治局常委" and "中共十九届一中全会" all have quantifiers "届", which are translated into "代", "期" and "回" respectively. The meaning is vague and should be uniformly translated into "期"; Among them, the translation of the last three proper nouns lacks the Chinese conjunction "第". The case auxiliary word "の" was added by mistake in the translation of "十八届中共中央政治局委员" and "日美安全体制". The "中国共产党中央委员会" did not write in the form of Japanese Ming Dynasty characters, but directly used simplified Chinese characters.

The full name of "中共十九届一中全会" is "中国共产党第十九届中央委员会第一次全体会议", in which "一" stands for "第一次", which is an ordinal word rather than a cardinal word. Machine translation does not produce a correct translation. The fundamental reason is that there are no "规则" for translating such words in machine translation. If we can formulate corresponding rules for such words (for example, 中共m'1届m2 中全会→第m1期中央委员会第m2回全体会议), the translation system must be able to translate well no matter how many plenary sessions of the CPC Central Committee.(Guan 2018:6-7)

===2.1.2Mistranslation of Polysemy===
original text Translation by Youdao reference translation

スタジオ摄影棚/工作室直播现场/演播厅

日中関係の話中日关系的故事就中日关系(话题)

溝水沟鸿沟

それでは日中の問題について質問のある方。那么对白天的问题有提问的人。关于中日问题的话题，举手提问。

私たちのクラスは20人ちょっとですが、我们班有20人左右，我们班二十多人的意见统一很难，

いろいろな意見が出て、まとめるのは大変です。但是又各种各样的意见，总结起来很困难。

一体どうやって、13億人もの人をまとめているんですか。到底是怎么处理13亿的人的呢？中国是怎样把13亿人凝聚在一起的？

In the original text, the word "スタジオ" appeared four times and was translated into "摄影棚" or "工作室" respectively, but the context is on-site interview, not the production site of photography or film. "話" has many semantics, such as "说话", "事情", "道理", etc. In accordance with the practice of the interview program, Premier Zhu Rongji was invited to answer five questions on the topic of China Japan relations. Obviously, the meaning of the word "故事" is very abrupt. The inherent Japanese word "日中" means "晌午、白天". At the same time, it is also the abbreviation of the names of the two countries. The machine failed to deal with it correctly according to the context. "溝" refers to the gap between China and Japan, not a "水沟". The former "まとめる" appears in the original text with the word "意见", which is intended to describe that it is difficult to unify everyone's opinions. The latter "まとめている" also refers to unifying the thoughts of 1.3 billion people, not "处理". Therefore, it is more appropriate to use "统一" and "处理" in human translation, rather than "总结意见" or "处理意见".(Zhang 2019:5)

Mistranslation of polysemy has always been a difficult problem in machine translation research. The translation of each word is correct, but it is often very different from the original expression in the context. Zhang Zhengzeng said that ambiguity is a common phenomenon in natural language. Its essence is that the same language form may have different meanings, which is also one of the differences between natural language and artificial language. Therefore, one of the difficulties faced by machine translation is language disambiguation (Zhang Zheng, 2005:60). In this regard, we can mark all the meanings of polysemous words and judge which meaning to choose by common collocation with other words. At the same time, strengthen the text recognition ability of the machine to avoid the translation inconsistent with the current context. In this way, we can avoid the mistake of "大酱" in the place where famous figures such as Deng Xiaoping should have appeared in the previous political articles.(Wang 2020:7-9)

===2.1.3Mistranslation of compound words===
Multi class words refer to a word with two or more parts of speech, also known as the same word and different classes.

original text Translation by Youdao reference translation

1998年江泽民主席曾经访问日本, 1998年の江沢民国家主席の日本訪問し、 1998年、江沢民総書記が日本を訪問し、かつ

同已故小渊首相签署了联合宣言。かつて同じ故小渕首相が署名した共同宣言亡くなられた小渕総理と宣言に調印されました

Chinese "同" has two parts of speech: prepositions and conjunctions: "故" has many parts of speech, such as nouns, verbs, adjectives and conjunctions. This directly affects the judgment of the machine at the source language level. The word "同" in the above table is used as a conjunction to indicate the other party of a common act. "故" is used as a verb with the semantic meaning of "死亡", which is a modifier of "小渊首相". The machine regards "同" as an adjective and "故" as a noun "原因", which leads to confusion in the structure and unclear semantics of the translation. Different from the polysemy problem, multi category words have at least two parts of speech, and there is often not only one meaning under each part of speech. In this regard, software R & D personnel should fully consider the existence of multi category words, so that the translation machine can distinguish the meaning of words on the basis of marking the part of speech, so as to select the translation through the context and the components of the word in the sentence. Of course, the realization of this function is difficult, and we need to give full play to the wisdom of R & D personnel.(Guan 2018:9-12)

===2.2 Syntactic mistranslation in Chinese Japanese machine translation===
===2.2.1Mistranslation of tenses===
original text：History is written by the people, and all achievements are attributed to the people.

Translation by Youdao：歴史は人民が書いたものであり、すべての成果は人民のためである。

reference translation：歴史は人民が綴っていくものであり、すべての成果は人民に帰することとなります。

The original sentence meaning is "历史是人民书写的历史" or "历史是人民书写的东西". When translated into Japanese, due to the influence of Japanese language habits, the formal noun "もの" should be supplemented accordingly. In this sentence, both the machine and the interpreter have translated correctly. However, the machine's recognition of "的" is biased, resulting in tense translation errors. The past, present and future will become "history", and this is a continuous action. The form translated as "~ ていく" not only reflects that the action is a continuous action, but also conforms to the tense and semantic information of the original text. In addition, the machine's treatment of the preposition "于" is also inappropriate. In the original text, "人民" is the recipient of action, not the target language. As the most obvious feature of isolated language, function words in Chinese play an important role in semantic expression, and their translation should be regarded as a focus of machine translation research.(Zuo 2021:8)

original text：李克强同志是十六届中共中央政治局常委,其他五位同志都是十六届中共中央政治局委员。

Translation by Youdao：李克強総理は第16代中国共産党中央政治局常務委員であり、他の５人の同志はいずれも16期の中国共産党中央政治局委員である。

reference translation：李克強同志は第16期中国共産党中央政治局常務委員を務め、他の５人は第16期中共中央政治局委員を務めました。

Judging the verb "是" in the original text plays its most basic positive role, but due to the complexity of Chinese language, "是" often can not be completely transformed into the form of "だ / である" in the process of translation. This sentence is a judgment of what has happened. Compared with the 19th session, the 18th session has become history. This is an implicit temporal information. It is very difficult for machines without human brain to recognize this implicit information. "中共中央政治局常委" is the abbreviation of "中共中央政治局常务委员会委员" and it is a kind of position. In Japanese, often use it with verbs such as "務める","担当する",etc. The translator adopts the past tense of "務める", which conforms to the expression habit of Japanese and deals with the problem of tense at the same time. However, machine translation only mechanically translates this sentence into judgment sentence, and fails to correctly deal with the past information implied by the word "十八届".(Guan 2018:4)

===2.2.2Mistranslation of honorifics===
Honorific language is a language means to show respect to the listener. Different from Japanese, there is no grammatical category of honorifics in Chinese. There is no specific fixed grammatical form to express honorifics, self modesty and politeness. Instead, specific words such as "您", "请" and "劳驾" are used to express all kinds of respect or self modesty. (Yang 2020:5-9)

Original text translation by Youdao reference translation

女士们，先生们，同志们，朋友们さんたち、先生たち、同志たち、お友达さん　　ご列席の皆さん

谢谢大家！ありがとうございます！ご清聴ありがとうございました。

これはどうされますか。这是怎么回事呢? 您将如何解决这一问题？

こうした問題をどうお考えでしょうか。我们会如何考虑这些问题呢？您如何看待这一问题？

For example, for the processing of "女士们，先生们，同志们，朋友们", the machine makes the translation correspond to the original one by one based on the principle of unchanged format, but there are errors in semantic communication and pragmatic habits. When speaking on formal occasions, Chinese expression tends to be comprehensive and detailed, as well as the address of the audience. In contrast, Japanese usually uses general terms such as "皆様", "ご臨席の皆さん" or "代表団の方々" as the opening remarks. In terms of Japanese Chinese translation, the machine also failed to recognize the usage of Japanese honorifics such as "される" and "お考え". It can be seen that Chinese Japanese machine translation has a low ability to deal with honorific expressions. The occasion is more formal. A good translation should not only be fluent in meaning, but also conform to the expression habits of the target language and match the current translation environment.(Che 2021:3-7)

===Conclusion===
In the process of discussing the Mistranslation of machine translation, this paper mainly cites the Mistranslation of Youdao translator. When I studied the problem of machine translation mistranslation, I also used a large number of translation software such as Google and Baidu for parallel comparison, and found that these translation software also had similar problems with Youdao translator. For example, the "新世界新未来" in Chinese ABAC structural phrases is translated by Baidu as "新し世界の新しい未来", which, like Youdao, is not translated in the form of parallel phrases; Google online translation translates the word "“全心全意" into a completely wrong "全面的に"; The original sentence "我吃了很多亏" in the Mistranslation of the unique expression in the language is translated by Google online as "私はたくさんの損失を食べました". Because the "吃" and "亏" in the original text are not closely adjacent, the machine can not recognize this echo and mistakenly treats "亏" as a kind of food, so the machine translates the predicate as "食べました"; Japanese "こうした問題をどう考えでしょうか", Google's online translation is "你如何看待这些问题?", "你" tone can not reflect the tone of Japanese honorific, while Baidu translates as "你怎么想这样的问题呢?" Although the meaning can be understood, it is an irregular spoken language. Google and Baidu also made the same mistakes as Youdao in the translation of proper nouns. For example, they translated "十七届(中共中央政治局常委)”" into "第17回..." .In short, similar mistranslations of Youdao are also common in Baidu and Google. Due to space constraints, they will not be listed one by one here.(Cui 2019:7)

Mr. Liu Yongquan, Institute of language, Chinese Academy of Social Sciences (1997) It has been pointed out that machine translation is a linguistic problem in the final analysis. Although corpus based machine translation does not require a lot of linguistic knowledge, language expression is ever-changing. Machine translation based solely on statistical ideas can not avoid the translation quality problems caused by the lack of language rules. The following is based on the analysis of lexical, syntactic and other mistranslations From the perspective of the characteristics of the source language, this paper summarizes some difficulties of Chinese and Japanese in machine translation.(Liu 2014:8)

(1) The difficulties of Chinese in machine translation

Chinese is a typical isolated language. The relationship between words needs to be reflected by word order and function words. We should pay attention to the transformation of function words such as "的", "在", "向" and "了". Some special verbs, such as "是", "做" and "作", are widely used. How to translate on the basis of conforming to Japanese pragmatic habits and expressions is a difficulty in machine translation research. In terms of word order, Chinese is basically "subject→predicate→object". At the same time, Chinese pays attention to parataxis, and there is no need to be clear in expression with meaningful cohesion, which increases the difficulty of Chinese Japanese machine translation. When there are multiple verbs or modifier components in complex long sentences, machine translation usually can not accurately divide the components of the sentence, resulting in the result that the translation is completely unreadable.(Guan 2018:6-12)

(2) Difficulties of Japanese in machine translation

Both Chinese and Japanese languages use Chinese characters, and most machines produce the target language through the corresponding translation of Chinese characters. However, pseudonyms in Japanese play an important role in judging the part of speech and meaning, and can not only recognize Chinese characters and judge the structure and semantics of sentences. Japanese vocabulary is composed of Chinese vocabulary, inherent vocabulary and foreign vocabulary. Among them, the first two have a great impact on Chinese Japanese machine translation. For example "提出" is translated as "提出する" or "打ち出す"; and "重视" is translated as "重視する" or "大切にする". Japanese is an adhesive language, which contains a lot of "けど", "が" and "けれども" Some of them are transitional and progressive structures, but there are also some sequential expressions that do not need translation, and these translation software often can not accurately grasp them.(Che 2021:10)

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Networking Linking

http://www.elecfans.com/rengongzhineng/692245.html

https://baike.baidu.com/item/%E6%9C%BA%E5%99%A8%E7%BF%BB%E8%AF%91/411793

=13 陈湘琼Chen Xiangqiong（Study on Post-editing from the Perspective of Functional Equivalence Theory ）=
[[Machine_Trans_EN_13]]

=14 Bi bi Nadia（Machine Translation a Challenge for Human Translators)=
[[Machine_Trans_EN_14]]

===Abstract===
Machine translation is a big obstacle in the way of Human translators or interpretors although it is quick and less time consuming.people are trying to get translation of their target language using through source language.For this purpose they are using digital apps like Google translation Google translation does not give accurate and exact interpretation.Google translator is translates word to word translate that doesn't clarifies it's true and actual meaning.On the other hand human translators can give exact and accurate translation ,they take care of grammatical errors , diction and sentence structure.They clarify the purpose of target language through using source language.

===Keywords===
Descriptive translation, academic, interdiscipline, comparative literature, localization,Translatology,school of thought,translation , studies, linguistics, corresponding.

===Body of article===
Translation is the process of reworking text from one language into another to maintain the original message and communication. But, like everything else, there are different methods of translation, and they vary in form and function. What is translation? The term has become widely used among knowledge transfer researchers and practitioners, especially in the fields of health and health care. In a landmark review, Jonathan Lomas began to argue that 'The tasks… may be defined as to establish and maintain links between researchers and their audience, via the appropriate translation of research findings' (Lomas 1997, p 4). In 2004, the World Health Organization's World Report on Knowledge for Better Health suggested that 'One of the key contributions of research to health systems is the translation of knowledge into actions' (WHO 2004, p 33 and p 100). By 2006, special issues of WHO's Bulletin as well as the journals Evaluation and the Health Professions and the Journal of Continuing Education in the Health Professions were dedicated to translation.But what does 'translation' mean? It may be a new word for an old problem, meaning nothing more than 'transfer'. The rapidly emerging field of 'translational medicine' seems to take translation to mean generally what transfer might have meant, that is the transmission of knowledge and evidence 'from bench to bedside'. As one commentator has observed, "Translational medicine" as a fashionable term is being increasingly used to describe the wish of biomedical researchers to ultimately help patients' (Wehling 2008, abstract).
Semantic uncertainty persists, not least because of the different interests of scientists, clinicians, patients and commercial firms (Littman et al 2007): 'Translational research means different things to different people, but it seems important to almost everyone' (Woolf 2008, p 211).
In related fields, such as public health (Armstrong et al 2006), 'translation' seems to signify dissatisfaction with 'transfer'. It wants to move away from thinking of knowledge transfer as a form of technology transfer or dissemination, rejecting if only by implication its mechanistic assumptions and its model of linear messaging from A to B. But still, what does it signify?

===Why translation?===
'Translation' indicates a closer attention to the problem of shared meaning and how it might be developed. It seems to represent some new epistemological lubricant, facilitating the dissemination of texts and the application and use of the knowledge and information they in. Simply, translation might be the key to transfer. And yet, when we stop to think, we are more ambivalent. What is translated often seems somehow inferior, not real or original. Note how readily commentators reach for the idea that things might be 'lost in translation'. Knowing at a distance – made in and mediated by translation - makes for incomplete renditions, blurred images, partial truths. So what might 'translation' really mean? The purpose of this paper is to set out, for policy makers and practitioners, the theoretical and conceptual resources translation holds and seems to represent. In doing so, it explores understandings of translation in the fields of literature and linguistics and in the sociology of science and technology. It begins by setting out just why this idea of translation should make immediate, intuitive sense in relation to research, policy and practice.
1translation in research, policy and practice research as translation
Research often entails translation from one language to another: where data is collected from more than one ethnic group, for example, or where the language of the researcher is other than that of the research subject. It may draw on a secondary literature or source documents written in different languages, and may be published and disseminated in languages other than the one in which it is first written up.
2In a different way, to conduct an interview is to ask for an account of experience and its meanings, but it is also to construct and translate that experience in terms defined at least in part by the researcher. In representing what is said, transcripts then select data, usually excluding significant gesture and eye-contact, for example. Often, certain characteristics of speech-acts (such as hesitations) will be edited out. In turn, the format of the transcript shapes the analytic use the researcher may make of it. The basis of research 'findings', then, is an artefact, a transcript or translation, not an original interaction (Ochs 1979, Barnes, Bloor and Henry 1996, Ross 2009).
3In this way, the researcher recasts aspects of his or her problem or topic in new, scientific form: 'All researchers "translate" the experiences of others' (Temple 1997, p 609). Research is invariably conducted in a sort of 'metalanguage' (Hantrais and Ager 1985): the research process can be conceived as one of successive translations (from theoretical formulation to operationalization, transcription, interpretation and dissemination). Theorization is a process of reciprocal back and forth between theory and fact, in which conceptions of each are revised in order that one fit the other (Baldamus 1974).
4 It is a kind of translation: a rereading, re-use, re-application or re-representation of what we know in new terms (Turner 1980). Referencing, too, is an act of translation, a form of appropriation and incorporation of one text by another (Gilbert 1977).policy as translation Each of the fields covered by the paper is diverse and ill-defined, and there is no intention here to provide a comprehensive account of any them. Sources have been chosen for their relevance: main references are cited in the text, and additional sources listed in footnotes.

2For a brief introduction to the technical issues involved in social research in more than one language, see Birbili (2000). For translation issues in survey research and question design in general, see Ervin and Bower (1952) and Deutscher (1968); on translating survey research instruments (in this instance health-related quality of life measures), Bowden and Fox-Rushby (2003). On the use of translators and interpreters, see Temple (1997) and Jentsch (1998).
3For an interesting discussion of this problem, see Bourdieu (1999), esp pp 621-626, 'The risks of writing'.
===Difference between machine translation and human translators===
Few people disagree on the differences between the two, but many argue over the quality of the translations. How accurate are machine translations? How reliable are human translations? Some say machine translation produces near-perfect translations while others are adamant that translations are incomprehensible and cause more problems than they solve. Results will, of course, vary depending on the source and target languages, the machine translation service used (e.g. Google Translate), and the complexity of the original text.
Machine translation, love it or hate it, is here to stay. In fact, the machine translation market is growing at such a fast pace that it is predicted to reach $980 million by 2022.
===Machine translation: the pros and cons===
The advantages of machine translation generally come down to two factors: it’s faster and cheaper. The downside to this is the standard of translation can be anywhere from inaccurate, to incomprehensible, and potentially dangerous (more on that shortly).
==The advantages of machine translation==
Many free tools are readily available (Google Translate, Skype Translator, etc.)
Quick turnaround time
You can translate between multiple languages using one tool
Translation technology is constantly improving
The disadvantages of machine translation
Level of accuracy can be very low
Accuracy is also very inconsistent across different languages
==Machines can't translate context ==
Mistakes are sometimes costly
Sometimes translation simply doesn’t work
The most important thing to consider with any kind of translation is the cost of potential mistakes. Translating instructions for medical equipment, aviation manuals, legal documents and many other kinds of content require 100% accuracy. In such cases, mistakes can cost lives, huge amounts of money and irreparable damage to your company’s image. So choose carefully!
Human translation: the pros and cons
Human translation essentially switches the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of mistakes. Alternatively, whether mistakes simply aren’t an option, like the cases we looked at in the previous section.

==The advantages of human translation ==
It’s a translator’s job to ensure the highest accuracy
Humans can interpret context and capture the same meaning, rather than simply translating words
Human translators can review their work and provide a quality process
Humans can interpret the creative use of language, e.g. puns, metaphors, slogans, etc.
Professional translators understand the idiomatic differences between their languages
Humans can spot pieces of content where literal translation isn’t possible and find the most suitable alternative
The disadvantages of human translation
Turnaround time is longer
Translators rarely work for free
Unless you use a translation agency, with access to thousands of translators, you’re limited to the languages any one translator can work with
Simply put, human translation is your best option when accuracy is even remotely important. Other considerations to make are the complexity of your source material and the two languages you’re translating between – both of which can render machines pretty useless.

When to use machine and human translation
The truth is, the debate over machine vs human translation is an unnecessary distraction. What we should really be talking about is when to use these two different types of translation services, because they both serve a very valid purpose.

Examples of when to use machine translation
When you have a large bulk of content to translate and the general meaning is enough
When your translation never reaches the final audience, e.g. you’re translating a resource as research for another piece of content
Translating documents for internal use within a company, provided 100% accuracy isn’t needed
To partially translate large chunks of content for a human translator to improve upon
Examples of when to use human translation
When accuracy is important
Most cases where your translated content is received by a consumer audience
When you have a duty of care to provide accurate translations (e.g. legal documents, product instructions, medical guidelines or health and safety content)
When translating marketing material or other texts for creative language uses.

types of machine translation.

What is Machine Translation? Rule Based Machine Translation vs. Statistical Machine Translation. Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology
Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.
The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.
Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.
In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology
Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT
Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Rule-Based MT Statistical MT
+ Consistent and predictable quality – Unpredictable translation quality
+ Out-of-domain translation quality – Poor out-of-domain quality
+ Knows grammatical rules – Does not know grammar
+ High performance and robustness – High CPU and disk space requirements
+ Consistency between versions – Inconsistency between versions
– Lack of fluency + Good fluency
– Hard to handle exceptions to rules + Good for catching exceptions to rules
– High development and customization costs + Rapid and cost-effective development costs provided the required corpus exists
Given the overall requirements, there is a clear need for a third approach through which users would reach better translation quality and high performance (similar to rule-based MT), with less investment (similar to statistical MT).
Post-Edited Machine Translation (PEMT)
Often, PEMT is used to bridge the gap between the speed of machine translation and the quality of human translation, as translators review, edit and improve machine-translated texts. PEMT services cost more than plain machine translations but less than 100% human translation, especially since the post-editors don’t have to be fluently bilingual—they just have to be skilled proofreaders with some experience in the language and target region.
Successful translation is about more than just the words, which is why we advocate for not just human translation by skilled linguists, but for translation by people deeply familiar with the cultures they’re writing for. Life experience, study and the knowledge that only comes from living in a geographic region can make the difference between words that are understandable and language that is capable of having real, positive impact.

PacTranz
The HUGE list of 51 translation types, methods and techniques
Upper section of infographic of 51 common types of translation classified in 4 broad categoriesThere are a bewildering number of different types of translation.
So we’ve identified the 51 types you’re most likely to come across, and explain exactly what each one means.
This includes all the main translation methods, techniques, strategies, procedures and areas of specialisation.
It’s our way of helping you make sense of the many different kinds of translation – and deciding which ones are right for you.
Don’t miss our free summary pdf download later in the article!
The 51 types of translation we’ve identified fall neatly into four distinct categories.
Translation Category A: 15 types of translation based on the technical field or subject area of the text
Icons representing 15 types of translation categorised by the technical field or subject area of the textTranslation companies often define the various kinds of translation they provide according to the subject area of the text.
This is a useful way of classifying translation types because specialist texts normally require translators with specialist knowledge.
Here are the most common types you’re like to come across in this category.

1. General Translation
What is it?
The translation of non-specialised text. That is, text that we can all understand without needing specialist knowledge in some area.
The text may still contain some technical terms and jargon, but these will either be widely understood, or easily researched.
What this means
The implication is that you don’t need someone with specialist knowledge for this type of translation – any professional translator can handle them.
Translators who only do this kind of translation (don’t have a specialist field) are sometimes referred to as ‘generalist’ or ‘general purpose’ translators.
Examples
Most business correspondence, website content, company and product/service info, non-technical reports.
Most of the rest of the translation types in this Category do require specialist translators.
Check out our video on 13 types of translation requiring special translator expertise:

2. Technical Translation
What is it?
We use the term “technical translation” in two different ways:
Broad meaning: any translation where the translator needs specialist knowledge in some domain or area.
This definition would include almost all the translation types described in this section.
Narrow meaning: limited to the translation of engineering (in all its forms), IT and industrial texts.
This narrower meaning would exclude legal, financial and medical translations for example, where these would be included in the broader definition.
What this means
Technical translations require knowledge of the specialist field or domain of the text.
That’s because without it translators won’t completely understand the text and its implications. And this is essential if we want a fully accurate and appropriate translation.Good to know Many technical translation projects also have a typesetting/dtp requirement. Be sure your translation provider can handle this component, and that you’ve allowed for it in your project costings and time frames.
Examples
Manuals, specialist reports, product brochures

3. Scientific Translation
What is it?
The translation of scientific research or documents relating to it.
What this means
These texts invariably contain domain-specific terminology, and often involve cutting edge research.
So it’s imperative the translator has the necessary knowledge of the field to fully understand the text. That’s why scientific translators are typically either experts in the field who have turned to translation, or professionally qualified translators who also have qualifications and/or experience in that domain.
On occasion the translator may have to consult either with the author or other domain experts to fully comprehend the material and so translate it appropriately.
Examples
Research papers, journal articles, experiment/trial results

4. Medical Translation
What is it?
The translation of healthcare, medical product, pharmaceutical and biotechnology materials.
Medical translation is a very broad term covering a wide variety of specialist areas and materials – everything from patient information to regulatory, marketing and technical documents.
As a result, this translation type has numerous potential sub-categories – ‘medical device translations’ and ‘clinical trial translations’, for example.
What this means
As with any text, the translators need to fully understand the materials they’re translating. That means sound knowledge of medical terminology and they’ll often also need specific subject-matter expertise.
Good to know
Many countries have specific requirements governing the translation of medical device and pharmaceutical documentation. This includes both your client-facing and product-related materials.
Examples
Medical reports, product instructions, labeling, clinical trial documentation

5. Financial Translation
What is it?
In broad terms, the translation of banking, stock exchange, forex, financing and financial reporting documents.
However, the term is generally used only for the more technical of these documents that require translators with knowledge of the field.
Any competent translator could translate a bank statement, for example, so that wouldn’t typically be considered a financial translation.
What this means
You need translators with domain expertise to correctly understand and translate the financial terminology in these texts.
Examples
Company accounts, annual reports, fund or product prospectuses, audit reports, IPO documentation

6. Economic Translations
What is it?
1. Sometimes used as a synonym for financial translations.
2. Other times used somewhat loosely to refer to any area of economic activity – so combining business/commercial, financial and some types of technical translations.
3. More narrowly, the translation of documents relating specifically to the economy and the field of economics.
What this means
As always, you need translators with the relevant expertise and knowledge for this type of translation.

7. Legal Translation
What is it?
The translation of documents relating to the law and legal process.
What this means
Legal texts require translators with a legal background.
That’s because without it, a translator may not:
– fully understand the legal concepts
– write in legal style
– understand the differences between legal systems, and how best to translate concepts that don’t correspond.
And we need all that to produce professional quality legal translations – translations that are accurate, terminologically correct and stylistically appropriate.
Examples
Contracts, legal reports, court judgments, expert opinions, legislation

8. Juridical Translation
What is it?
1. Generally used as a synonym for legal translations.
2. Alternatively, can refer to translations requiring some form of legal verification, certification or notarization that is common in many jurisdictions.

9. Judicial Translation
What is it?
1. Most commonly a synonym for legal translations.
2. Rarely, used to refer specifically to the translation of court proceeding documentation – so judgments, minutes, testimonies, etc.

10. Patent Translation
What is it?
The translation of intellectual property and patent-related documents.
Key features
Patents have a specific structure, established terminology and a requirement for complete consistency throughout – read more on this here. These are key aspects to patent translations that translators need to get right.
In addition, subject matter can be highly technical.
What this means
You need translators who have been trained in the specific requirements for translating patent documents. And with the domain expertise needed to handle any technical content.
Examples
Patent specifications, prior art documents, oppositions, opinions

11. Literary Translation
What is it?
The translation of literary works – novels, short stories, plays, essays, poems.
Key features
Literary translation is widely regarded as the most difficult form of translation.
That’s because it involves much more than simply conveying all meaning in an appropriate style. The translator’s challenge is to also reproduce the character, subtlety and impact of the original – the essence of what makes that work unique.
This is a monumental task, and why it’s often said that the translation of a literary work should be a literary work in its own right.
What this means
Literary translators must be talented wordsmiths with exceptional creative writing skills.
Because few translators have this skillset, you should only consider dedicated literary translators for this type of translation.

12. Commercial Translation
What is it?
The translation of documents relating to the world of business.
This is a very generic, wide-reaching translation type. It includes other more specialised forms of translation – legal, financial and technical, for example. And all types of more general business documentation.
Also, some documents will require familiarity with business jargon and an ability to write in that style.
What this means
Different translators will be required for different document types – specialists should handle materials involving technical and specialist fields, whereas generalist translators can translate non-specialist materials.
Examples
Business correspondence, reports, marketing and promotional materials, sales proposals

13. Business Translations
What is it?
A synonym for Commercial Translations.

14. Administrative Translations
What is it?
The translation of business management and administration documents.
So it’s a subset of business / commercial translations.
What this means
The implication is these documents will include business jargon and ‘management speak’, so require a translator familiar with, and practised at, writing in that style.
Examples
Management reports and proposals

15. Marketing Translations
What is it?
The translation of advertising, marketing and promotional materials.
This is a subset of business or commercial translations.
Key features
Marketing copy is designed to have a specific impact on the audience – to appeal and persuade.
So the translated copy must do this too.
But a direct translation will seldom achieve this – so translators need to adapt their wording to produce the impact the text is seeking.
And sometimes a completely new message might be needed – see transcreation in our next category of translation types.
What this means
Marketing translations require translators who are skilled writers with a flair for producing persuasive, impactful copy.
As relatively few translators have these skills, engaging the right translator is key.
Good to know
This type of translation often comes with a typesetting or dtp requirement – particularly for adverts, posters, brochures, etc.
Its best for your translation provider to handle this component. That’s because multilingual typesetters understand the design and aesthetic conventions in other languages/cultures. And these are essential to ensure your materials have the desired impact and appeal in your target markets.
Examples
Advertising, brochures, some website/social media text.
Translation Category B: 14 types of translation based on the end product or use of the translation
This category is all about how the translation is going to be used or the end product that’s produced.
Most of these types involve either adapting or processing a completed translation in some way, or converting or incorporating it into another program or format.
You’ll see that some are very specialised, and complex.
It’s another way translation providers refer to the range of services they provide.
Check out our video of the most specialised of these types of translation:

16. Document Translations
What is it?
The translation of documents of all sorts.
Here the translation itself is the end product and needs no further processing beyond standard formatting and layout.

17. Text Translations
What is it?
A synonym for document translation.

18. Certified Translations
What is it?
A translation with some form of certification.
Key features
The certification can take many forms. It can be a statement by the translation company, signed and dated, and optionally with their company seal. Or a similar certification by the translator.
The exact format and wording will depend on what clients and authorities require – here’s an example.

19. Official Translations
What is it?
1. Generally used as a synonym for certified translations.
2. Can also refer to the translation of ‘official’ documents issued by the authorities in a foreign country. These will almost always need to be certified.

20. Software Localisation
What is it?
Adapting software for another language/culture.
Key features
The goal of software localisation is not just to make the program or product available in other languages. It’s also about ensuring the user experience in those languages is as natural and effective as possible.
Translating the user interface, messaging, documentation, etc is a major part of the process.
Also key is a customisation process to ensure everything matches the conventions, norms and expectations of the target cultures.
Adjusting time, date and currency formats are examples of simple customisations. Others might involve adapting symbols, graphics, colours and even concepts and ideas.
Localisation is often preceded by internationalisation – a review process to ensure the software is optimally designed to handle other languages.
And it’s almost always followed by thorough testing – to ensure all text is in the correct place and fits the space, and that everything makes sense, functions as intended and is culturally appropriate.
Localisation is often abbreviated to L10N, internationalisation to i18n.
What this means
Software localisation is a specialised kind of translation, and you should always engage a company that specialises in it.
They’ll have the systems, tools, personnel and experience needed to achieve top quality outcomes for your product.

21. Game Localisation
What is it?
Adapting games for other languages and markets.

It’s a subset of software localisation.
Key features
The goal of game localisation is to provide an engaging and fun gaming experience for speakers of other languages.

It involves translating all text and recording any required foreign language audio.

But also adapting anything that would clash with the target culture’s customs, sensibilities and regulations.

For example, content involving alcohol, violence or gambling may either be censored or inappropriate in the target market.

And at a more basic level, anything that makes users feel uncomfortable or awkward will detract from their experience and thus the success of the game in that market.

So portions of the game may have to be removed, added to or re-worked.

Game localisation involves at least the steps of translation, adaptation, integrating the translations and adaptations into the game, and testing.

What this means
Game localisation is a very specialised type of translation best left to those with specific expertise and experience in this area.

22. Multimedia Localisation
What is it?
Adapting multimedia for other languages and cultures.

Multimedia refers to any material that combines visual, audio and/or interactive elements. So videos and movies, on-line presentations, e-Learning courses, etc.
Key features
Anything a user can see or hear may need localising.

That means the audio and any text appearing on screen or in images and animations.

Plus it can mean reviewing and adapting the visuals and/or script if these aren’t suitable for the target culture.

The localisation process will typical involve:
– Translation
– Modifying the translation for cultural reasons and/or to meet technical requirements
– Producing the other language versions

Audio output may be voice-overs, dubbing or subtitling.

And output for visuals can involve re-creating elements, or supplying the translated text for the designers/engineers to incorporate.

What this means
Multimedia localisation projects vary hugely, and it’s essential your translation providers have the specific expertise needed for your materials.

23. Script Translations
What is it?
Preparing the text of recorded material for recording in other languages.
Key features
There are several issues with script translation.

One is that translations typically end up longer than the original script. So voicing the translation would take up more space/time on the video than the original language.

Sometimes that space will be available and this will be OK.

But generally it won’t be. So the translation has to be edited back until it can be comfortably voiced within the time available on the video.

Another challenge is the translation may have to synchronise with specific actions, animations or text on screen.

Also, some scripts also deal with technical subject areas involving specialist technical terminology.

Finally, some scripts may be very culture-specific – featuring humour, customs or activities that won’t work well in another language. Here the script, and sometimes also the associated visuals, may need to be adjusted before beginning the translation process.

It goes without saying that a script translation must be done well. If it’s not, there’ll be problems producing a good foreign language audio, which will compromise the effectiveness of the video.

Translators typically work from a time-coded transcript. This is the original script marked to show the time available for each section of the translation.

What this means
There are several potential pitfalls in script translations. So it’s vital your translation provider is practiced at this type of translation and able to handle any technical content.

24. Voice-over and Dubbing Projects
What is it?
Translation and recording of scripts in other languages.

Voice-overs vs dubbing
There is a technical difference.
A voice-over adds a new track to the production, dubbing replaces an existing one.

Key features
These projects involve two parts:
– a script translation (as described above), and
– producing the audio

So they involve the combined efforts of translators and voice artists.
The task for the voice artist is to produce a high quality read. That’s one that matches the style, tone and richness of the original.

Often each section of the new audio will need to be the same length as the original.

But sometimes the segments will need to be shorter – for example where the voice-over lags the original by a second or two. This is common in interviews etc, where the original voice is heard initially then drops out.

The most difficult form of dubbing is lip-syncing – where the new audio needs to synchronise with the original speaker’s lip movements, gestures and actions.

Lip-syncing requires an exceptionally skilled voice talent and considerable time spent rehearsing and fine tuning the translation.

What this means
You need to use experienced professionals every step of the way in this type of project.

That’s to ensure firstly that your foreign-language scripts are first class, then that the voicing is of high professional standard.

Anything less will mean your foreign language versions will be way less effective and appealing to your target audience.

25. Subtitle Translations
What is it?
Producing foreign language captions for sub or surtitles.
Key features
The goal with subtitling is to produce captions that viewers can comfortably read in the time available and still follow what’s happening on the video.

To achieve this, languages have “rules” governing the number of characters per line and the minimum time each subtitle should display.

Sticking to these guidelines is essential if your subtitles are to be effective.

But this is no easy task – it requires simple language, short words, and a very succinct style. Translators will spend considerable time mulling over and re-working their translation to get it just right.

Most subtitle translators use specialised software that will output the captions in the format sound engineers need for incorporation into the video.

What this means
As with other specialised types of translation, you should only use translators with specific expertise and experience in subtitling.

26. Website Localisation
What is it?
The translation and adapting of relevant content on a website to best suit the target language and culture.

Note: Many providers use the term website translation as a synonym for localisation. Strictly speaking though, translation is just one part of localisation.
Key features

Not all pages on a website may need to be localised – clients should review their content to identify what’s relevant for the other language versions.
Some content may need specialist translators – legal and technical pages for example.
There may also be videos, linked documents, and text or captions in graphics to translate.
Adaptation can mean changing date, time, currency and number formats, units of measure, etc.
But also images, colours and even the overall site design and style if these won’t have the desired impact in the target culture.
Translated files can be supplied in a wide range of formats – translators usually coordinate output with the site webmasters.
New language versions are normally thoroughly reviewed and tested before going live to confirm everything is displaying correctly, works as intended and is cultural appropriate.
What this means
The first step should be to review your content and identify what needs to be translated. This might lead you to modify some pages for the foreign language versions.

In choosing your translation providers be sure they can:
– handle any technical or legal content,
– provide your webmaster with the file types they want.

And you should always get your translators to systematically review the foreign language versions before going live.

27. Transcreation
What is it?
Adapting a message to elicit the same emotional response in another language and culture.
Translation is all about conveying the message or meaning of a text in another language. But sometimes that message or meaning won’t have the desired effect in the target culture.

This is where transcreation comes in. Transcreation creates a new message that will get the desired emotional response in that culture, while preserving the style and tone of the original.

So it’s a sort of creative translation – which is where the word comes from, a combination of ‘translation’ and ‘creation’.

At one level transcreation may be as simple as choosing an appropriate idiom to convey the same intent in the target language – something translators do all the time.

But mostly the term is used to refer to adapting key advertising and marketing messaging. Which requires copywriting skills, cultural awareness and an excellent knowledge of the target market.

Who does it?
Some translation companies have suitably skilled personnel and offer transcreation services.

Often though it’s done in the target country by specialist copywriters or an advertising or marketing agency – particularly for significant campaigns and to establish a brand in the target marketplace.

What this means
Most general marketing and promotional texts won’t need transcreation – they can be handled by a translator with excellent creative writing skills.

But slogans, by-lines, advertising copy and branding statements often do.

Whether you should opt for a translation company or an in-market agency will depend on the nature and importance of the material, and of course your budget.

28. Audio Translations
What is it?
Broad meaning: the translation of any type of recorded material into another language.

More commonly: the translation of a foreign language video or audio recording into your own language. So this is where you want to know and document what a recording says.
Key features
The first challenge with audio translations is it’s often impossible to pick up every word that’s said. That’s because audio quality, speech clarity and speaking speed can all vary enormously.

It’s also a mentally challenging task to listen to an audio and translate it directly into another language. It’s easy to miss a word or an aspect of meaning.

So best practice is to first transcribe the audio (type up exactly what is said in the language it is spoken in), then translate that transcription.

However, this is time consuming and therefore costly, and there are other options if lesser precision is acceptable.

What this means
It’s best to discuss your requirements for this kind of translation with your translation provider. They’ll be able to suggest the best translation process for your needs.

Examples
Interviews, product videos, police recordings, social media videos.

29. Translations with DTP
What is it?
Translation incorporated into graphic design files.multilingual dtp example in the form of a Rubik's Cube with foreign text on each square
Key features
Graphic design programs are used by professional designers and graphic artists to combine text and images to create brochures, books, posters, packaging, etc.

Translation plus dtp projects involve 3 steps – translation, typesetting, output.

The typesetting component requires specific expertise and resources – software and fonts, typesetting know-how, an appreciation of foreign language display conventions and aesthetics.

What this means
Make sure your translation company has the required multilingual typesetting/desktop publishing expertise whenever you’re translating a document created in a graphic design program.

Translation Category C: 13 types of translation based on the translation method employed
This category has two sub-groups:
– the practical methods translation providers use to produce their translations, and
– the translation strategies/methods identified and discussed within academia.

The translation methods translation providers use
There are 4 main methods used in the translation industry today. We have an overview of each below, but for more detail, including when to use each one, see our comprehensive blog article.

Or watch our video.

Important: If you’re a client you need to understand these 4 methods – choose the wrong one and the translation you end up with may not meet your needs!

30. Machine Translation (MT)
What is it?
A translation produced entirely by a software program with no human intervention.

A widely used, and free, example is Google Translate. And there are also commercial MT engines, generally tailored to specific domains, languages and/or clients.

Pros and cons
There are two limitations to MT:
– they make mistakes (incorrect translations), and
– quality of wording is patchy (some parts good, others unnatural or even nonsensical)

On they positive side they are virtually instantaneous and many are free.

Best suited for:
Getting the general idea of what a text says.

This method should never be relied on when high accuracy and/or good quality wording is needed.

31. Machine Translation plus Human Editing (PEMT)
What is it?
A machine translation subsequently edited by a human translator or editor (often called Post-editing Machine Translation = PEMT).

The editing process is designed to rectify some of the deficiencies of a machine translation.

This process can take different forms, with different desired outcomes. Probably most common is a ‘light editing’ process where the editor ensures the text is understandable, without trying to fix quality of expression.

Pros and cons
This method won’t necessarily eliminate all translation mistakes. That’s because the program may have chosen a wrong word (meaning) that wasn’t obvious to the editor.

And wording won’t generally be as good as a professional human translator would produce.

Its advantage is it’s generally quicker and a little cheaper than a full translation by a professional translator.

Best suited for:
Translations for information purposes only.

Again, this method shouldn’t be used when full accuracy and/or consistent, natural wording is needed.

32. Human Translation
What is it?
Translation by a professional human translator.
Pros and cons
Professional translators should produce translations that are fully accurate and well-worded.

That said, there is always the possibility of ‘human error’, which is why translation companies like us typically offer an additional review process – see next method.

This method will take a little longer and likely cost more than the PEMT method.

Best suited for:
Most if not all translation purposes.

33. Human Translation + Revision
What is it?
A human translation with an additional review by a second translator.

The review is essentially a safety check – designed to pick up any translation errors and refine wording if need be.

Pros and cons
This produces the highest level of translation quality.

It’s also the most expensive of the 4 methods, and takes the longest.

Best suited for:
All translation purposes.

Gearwheel with 5 practical translation methods written on the teeth
There’s also one other common term used by practitioners and academics alike to describe a type (method) of translation:

34. Computer-Assisted Translation (CAT)
What is it?
A human translator using computer tools to aid the translation process.

Key features
Virtually all translators use such tools these days.

The most prevalent tool is Translation Memory (TM) software. This creates a database of previous translations that can be accessed for future work.

TM software is particularly useful when dealing with repeated and closely-matching text, and for ensuring consistency of terminology. For certain projects it can speed up the translation process.

The translation methods described by academia
A great deal has been written within academia analysing how human translators go about their craft.

Seminal has been the work of Newmark, and the following methods of translation attributed to him are widely discussed in the literature.Gearwheel with Newmark's 8 translation methods written on the teeth
These methods are approaches and strategies for translating the text as a whole, not techniques for handling smaller text units, which we discuss in our final translation category.

35. Word-for-word Translation
This method translates each word into the other language using its most common meaning and keeping the word order of the original language.

So the translator deliberately ignores context and target language grammar and syntax.

Its main purpose is to help understand the source language structure and word use.

Often the translation will be placed below the original text to aid comparison.

36. Literal Translation
Words are again translated independently using their most common meanings and out of context, but word order changed to the closest acceptable target language grammatical structure to the original.

Its main suggested purpose is to help someone read the original text.

37. Faithful Translation
Faithful translation focuses on the intention of the author and seeks to convey the precise meaning of the original text.

It uses correct target language structures, but structure is less important than meaning.

38. Semantic Translation
Semantic translation is also author-focused and seeks to convey the exact meaning.

Where it differs from faithful translation is that it places equal emphasis on aesthetics, ie the ‘sounds’ of the text – repetition, word play, assonance, etc.

In this method form is as important as meaning as it seeks to “recreate the precise flavour and tone of the original” (Newmark).slide showing definition of semantic translation as a translation method

39. Communicative Translation
Seeks to communicate the message and meaning of the text in a natural and easily understood way.

It’s described as reader-focused, seeking to produce the same effect on the reader as the original text.

A good comparison of Communicative and Semantic translation can be found here.

40. Free Translation
Here conveying the meaning and effect of the original are all important.

There are no constraints on grammatical form or word choice to achieve this.

Often the translation will paraphrase, so may be of markedly different length to the original.

41. Adaptation
Mainly used for poetry and plays, this method involves re-writing the text where the translation would otherwise lack the same resonance and impact on the audience.

Themes, storylines and characters will generally be retained, but cultural references, acts and situations adapted to relevant target culture ones.

So this is effectively a re-creation of the work for the target culture.

42. Idiomatic Translation
Reproduces the meaning or message of the text using idioms and colloquial expressions and language wherever possible.

The goal is to produce a translation with language that is as natural as possible.

Translation Category D: 9 types of translation based on the translation technique used
These translation types are specific strategies, techniques and procedures for dealing with short chunks of text – generally words or phrases.

They’re often thought of as techniques for solving translation problems.

They differ from the translation methods of the previous category which deal with the text as a whole.
9 translation techniques as titles of books in a bookcase

43. Borrowing
What is it?
Using a word or phrase from the original text unchanged in the translation.

Key features
With this procedure we don’t translate the word or phrase at all – we simply ‘borrow’ it from the source language.

Borrowing is a very common strategy across languages. Initially, borrowed words seem clearly ‘foreign’, but as they become more familiar, they can lose that ‘foreignness’.

Translators use this technique:
– when it’s the best word to use – either because it has become the standard, or it’s the most precise term, or
– for stylist effect – borrowings can add a prestigious or scholarly flavour.

Borrowed words or phrases are often italicised in English.

Examples of borrowings in English
grand prix, kindergarten, tango, perestroika, barista, sampan, karaoke, tofu

44. Transliteration
What is it?
Reproducing the approximate sounds of a name or term from a language with a different writing system.

Key features
In English we use the Roman (Latin) alphabet in common with many other languages including almost all European languages.

Other writing systems include Arabic, Cyrillic, Chinese, Japanese, Korean, Thai, and the Indian languages.

Transliteration from such systems into the Roman alphabet is also called romanisation.

There are accepted systems for how individual letters/sounds should be romanised from most other languages – there are three common systems for Chinese, for example.

English borrowings from languages using non-Roman writing systems also require transliteration – perestroika, sampan, karaoke, tofu are examples from the above list.

Translators mostly use transliteration as a procedure for translating proper names.

Examples
毛泽东 Mao Tse-tung or Mao Zedong
Владимир Путин Vladimir Putin
서울 Seoul
ភ្នំពេញ Phnom Penh

45. Calque or Loan Translation
What is it?
A literal translation of a foreign word or phrase to create a new term with the same meaning in the target language.

So a calque is a borrowing with translation if you like. The new term may be changed slightly to reflect target language structures.

Examples
German ‘Kindergarten’ has been calqued as детский сад in Russian, literally ‘children garden’ in both languages.

Chinese 洗腦 ‘wash’ + ‘brain’ is the origin of ‘brainwash’ in English.

English skyscraper is calqued as gratte-ciel in French and rascacielos in Spanish, literally ‘scratches sky’ in both languages.

46. Word-for-word translation
What is it?
A literal translation that is natural and correct in the target language.

Alternative names are ‘literal translation’ or ‘metaphrase’.

Note: this technique is different to the translation method of the same name, which does not produce correct and natural text and has a different purpose.

Key features
This translation strategy will only work between languages that have very similar grammatical structures.

And even then, only sometimes.

For example, standard word order in Turkish is Subject-Object-Verb whereas in English it’s Subject-Verb-Object. So a literal translation between these two will seldom work:
– Yusuf elmayı yedi is literally ‘Joseph the apple ate’.

When word-for-word translations don’t produce natural and correct text, translators resort to some of the other techniques described below.
Examples
French ‘Quelle heure est-il?’ works into English as ‘What time is it?’.

Russian ‘Oн хочет что-нибудь поесть’ is ‘He wants something to eat’.

47. Transposition
What is it?
Translation with a change of grammatical structure.

This technique gives the translation more natural wording and/or makes it grammatically correct.

Examples
A change in word order:
Our Turkish example Yusuf elmayı yedi (literally ‘Joseph the apple ate’) –> Joseph ate the apple.

Spanish La Casa Blanca (literally ‘The House White’) –> The White House

A change in grammatical category:
German Er hört gerne Musik (literally ‘he listens gladly [to] music’)
= subject pronoun + verb + adverb + noun
becomes Spanish Le gusta escuchar música (literally ‘[to] him [it] pleases to listen [to] music’)
= indirect object pronoun + verb + infinitive + noun
and English He likes listening to music
= subject pronoun + verb + gerund + noun.

48. Modulation
What is it?
Translation with a change of focus or point of view in the target language.

This technique makes the translation more idiomatic – how people would normally say it in the language.

Examples
English talks of the ‘top floor’ of a building, French the dernier étage = last floor. ‘Last floor’ would be unnatural in English, so too ‘top floor’ in French.

German uses the term Lebensgefahr (literally ‘danger to life’) where in English we’d be more likely to say ‘risk of death’.
In English we’d say ‘I dropped the key’, in Spanish se me cayó la llave, literally ‘the key fell from me’. The English perspective is that I did something (dropped the key), whereas in Spanish something happened to me – I’m the recipient of the action.

49. Equivalence or Reformulation
What is it?
Translating the underlying concept or meaning using a totally different expression.

This technique is widely used when translating idioms and proverbs.

And it’s common in titles and advertising slogans.

It’s a common strategy where a direct translation either wouldn’t make sense or wouldn’t resonate in the same way.

Examples
Here are some equivalents of the English saying “Pigs may fly”, meaning something will never happen, or “you’re being unrealistic” (Source):
– Thai: ชาติหน้าตอนบ่าย ๆ – literally, ‘One afternoon in your next reincarnation’
– French: Quand les poules auront des dents – literally, ‘When hens have teeth’
– Russian, Когда рак на горе свистнет – literally, ‘When a lobster whistles on top of a mountain’
– Dutch, Als de koeien op het ijs dansen – literally, ‘When the cows dance on the ice’
– Chinese: 除非太陽從西邊出來！– literally, ‘Only if the sun rises in the west’

50. Adaptation
What is it?
A translation that substitutes a culturally-specific reference with something that’s more relevant or meaningful in the target language.

It’s also known as cultural substitution or cultural equivalence.

It’s a useful technique when a reference wouldn’t be understood at all, or the associated nuances or connotations would be lost in the target language.

Note: the translation method of the same name is a similar concept but applied to the text as a whole.

Examples
Different cultures celebrate different coming of age birthdays – 21 in many cultures, 20, 15 or 16 in others. A translator might consider changing the age to the target culture custom where the coming of age implications were important in the original text.
Animals have different connotations across languages and cultures. Owls for example are associated with wisdom in English, but are a bad omen to Vietnamese. A translator might want to remove or amend an animal reference where this would create a different image in the target language.

51. Compensation
What is it?
A meaning or nuance that can’t be directly translated is expressed in another way in the text.
Example
Many languages have ways of expressing social status (honorifics) encoded into their grammatical structures.

So you can convey different levels of respect, politeness, humility, etc simply by choosing different forms of words or grammatical elements.
But these nuances will be lost when translating into languages that don’t have these structures.
Then translating into languages that don’t have these structures
Then translating into languages that don’t have these structures.

===Conclusion ===

In the light of above mentioned facts and figures here by we would say that machine translation is challenge for human translators because it can reduces the workload of translation but can't give accurate and exact translation of the target language.It can be less reliable than human translation..