Machine Trans EN 9

Machine Translation - A challenge or a chance for human translators?

Overview Page of Machine Translation

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To the To Do list 9 谢佳芬（人工智能时代下的机器翻译与人工翻译） Machine_Trans_EN_9

Abstract

With the continuous development of information technology, many industries are facing the competitive pressure of artificial intelligence, and so is the field of translation. Artificial intelligence technology has developed rapidly and combined with the field of translation，which has brought great impact and changes to traditional translation, but artificial intelligence translation and artificial translation have their own advantages and disadvantages. Artificial translation is in the leading position in adapting to human language logical habits and understanding characteristics, but in terms of translation threshold and economic value, the efficiency of artificial intelligence translation is even better. In a word, we need to know that machine translation and human translation are complementary rather than antagonistic.

Key Words

Machine Translation; Artificial Translation; Artificial Intelligence

题目

人工智能时代下的机器翻译与人工翻译

摘要

伴随着信息技术的不断发展，多个行业面临着人工智能的竞争压力，翻译领域也是如此。人工智能技术快速发展并与翻译领域结合，人工智能翻译给传统翻译带来了巨大的冲击和变革，但人工智能翻译与人工翻译存在着各自的优劣特点和发展空间，在适应人类语言逻辑习惯和理解特点的翻译效果上，人工翻译处于领先地位，但在翻译门槛和经济价值上，人工智能翻译的效率则更胜一筹。总的来说，我们要知道机器翻译与人工翻译是互补而非对立的关系。

关键词

机器翻译;人工翻译;人工智能

1. Introduction

1.1 The History of Machine Translation Aborad

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, the Soviet inventor Troyansky designed a machine to translate one language into another. [1]In 1946, the world's first modern electronic computer ENIAC was born. Soon after, American scientist Warren Weaver, a pioneer of information theory, put forward the idea of automatic language translation by computer in 1947. In 1949, Warren Weaver published a memorandum entitled Translation, which formally raised the issue of machine translation. In 1954, Georgetown University, with the cooperation of IBM, completed the English-Russian machine translation experiment with IBM-701 computer for the first time, which opened the prelude of machine translation research. [2] In 2006, Google translation was officially released as a free service software, bringing a big upsurge of statistical machine translation research. It was Franz Och who joined Google in 2004 and led Google translation. What’s more, it is precisely because of the unremitting efforts of generations of scientists that science fiction has been brought into reality step by step.

1.2 The History of Machine Translation in China

In 1956, the research and development of machine translation has been named in the scientific and technological work and made little achievements in China. On the eve of the tenth anniversary of the National Day in 1959, our country successfully carried out experiments, which translated nine different types of complicated sentences on large general-purpose electronic computers. The dictionary includes 2030 entries, and the grammar rule system consists of 29 circuit diagrams. [3]. After a period of stagnation, China's machine translation ushered in a high-speed development stage after the 1980s in the wave of the third scientific and technological revolution. With the rapid development of economy and science and technology, China has made a qualitative leap in the field of machine translation research with the pace of reform and opening up. In 1978, Institute of Scientific and Technological Information of China, Institute of Computing Technology and Institute of Linguistics carried out an English-Chinese translation experiment with 20 Metallurgical Title examples as the objects and achieved satisfactory results. Subsequently, they developed a JYE-I machine translation system, which based on 200 sentences from metallurgical documents. Its principles and methods were also widely used in the machine translation system developed in the future. In addition, the research achievements of machine translation in China during the 1980s and 1990s also include that Institute of Post and Telecommunication Sciences developed a machine translation system, C Retrieval and automatic typesetting system with good performance and strong practicability in October 1986; In 1988, ISTC launched the ISTIC-I English-Chinese Title System for the translation of applied literature of metallurgy, Information Research Institute of Railway developed an English-Chinese Title Recording machine translation system for railway documents; the Language Institute of the Academy of Social Sciences developed "Tianyu" English-Chinese machine translation system and Matr English-Chinese machine translation system developed by the computer department of National University of Defense Technology. After many explorations and studies, machine translation in China has gradually moved towards application, popularization and commercialization. China Software Technology Corporation launched "Yixing I" in 1988, marking China's machine translation system officially going to the market. After "Yixing", a series of machine translation systems such as Gaoli system in Beijing, Tongyi system in Tianjin and Langwei system in Shaanxi have also entered the public. In the 21st century, the development of a series of apps such as Kingsoft Powerword, Youdao translation and Baidu translation has greatly met the needs of ordinary users for translation. According to the working principle, machine translation has roughly experienced three stages: rule-based machine translation, statistics-based machine translation and deep learning based neural machine translation. [4] These three stages witnessed a leap in the quality of machine translation. Machine translation is more and more used in daily life and even the translation of some texts is almost comparable to artificial translation. In addition to text translation, voice translation, photo translation and other functions have also been listed, which provides great convenience for people's life. It is undeniable that machine translation has become the development trend of translation in the future.

1.3 The Status Quo of Machine Translation

In this big data era of information explosion, the prospect of machine translation is also bright. At present, the circular neural network system launched by Google has supported universal translation in more than 60 languages. Many Internet companies such as Microsoft Bing, Sogou, Tencent, Baidu and NetEase Youdao have also launched their own Internet free machine translation systems. [5] Users can obtain translation results free of charge by logging in to the corresponding websites. At present, the circular neural network translation system launched by Google can support real-time translation of more than 60 languages, and the domestic Baidu online machine translation system can also support real-time translation of 28 languages. These Internet online machine translation systems are suitable for a variety of terminal platforms such as mobile phone, PC, tablet and web and its functions are also quite diverse, supporting many translation forms, such as screen word selection, text scanning translation, photo translation, offline translation, web page translation and so on. Although its translation quality needs to be improved, it has been outstanding in the fields of daily dialogue, news translation and so on.

2. Advantages and Disadvantages of Machine Translation

Generally speaking, machine translation has the characteristics of high efficiency, low cost, accurate term translation and great development potential and etc. Machine translation is fast and efficient, this is something that artificial translation can’t catch up with. In addition, with the continuous emergence of all kinds of translation software in the market, compared with artificial translation, machine translation is cheap and sometimes even free, which greatly saves the economic cost and time for users with low translation quality requirements. What's more, compared with artificial translation, machine translation has a huge corpus, which makes the translation of some terms, especially the latest scientific and technological terms, more rapid and accurate. The accurate translation of these terms requires the translator to constantly learn, but learning needs a process, which has a certain test on the translator's learning ability and learning speed. In this regard, artificial translation has uncertainty and hysteretic nature. At the same time, with the progress of science and technology and the development of society, the function of machine translation will be more perfect and the quality of translation will be better.Today's machine translation tools and software are easy to carry, all you need to do is just to use the software and electronic dictionary in the mobile phone. There is no need to carry paper dictionaries and books for translation, which saves time and space. At the same time, machine translation covers many fields and is suitable for translation practice in different situations, such as academic, education, commercial trade, social networking, tourism, production technology, etc, it is also easy to deal with various professional terms. However, due to the limitation of translators' own knowledge, artificial translation is often limited to one or a few fields or industries. For example, it is difficult for an interpreter specializing in medical English to translate legal English. At the same time, machine translation also has its limitations. At first, machine can only operate word to word translation, which only plays the function and role of dictionary. Then, the application of syntax enables the process of sentence translation and it can be solved by using the direct translation method. When the original text and the target language are highly similar, it can be translated directly. For example, the original text "他是个老师." The target language is "he is a teacher ". With the increase of the structural complexity of the original text, the effect of machine translation is greatly reduced. Therefore, at the syntactic level, machine translation still stays in sentences with relatively simple structure. Meanwhile, the original text and the results of machine translation cannot be interchanged equally, indicating that English-Chinese translation has strong randomness, and is not rigorous and scientific enough. Nowadays, machine translation is highly dependent on parallel corpora, but the construction of parallel corpora is not perfect. At present, the resources of some mainstream languages such as Chinese and English are relatively rich, while the data collection of many small languages is not satisfactory. Moreover, the current corpus is mainly concentrated in the fields of government literature, science and technology, current affairs and news, while there is a serious lack of data in other fields, which can’t reflect the advantages of machine translation. At the same time, corpus construction lags behind. Some informative texts introducing the latest cutting-edge research results often spread the latest academic knowledge and use a large number of new professional terms, such as academic papers and teaching materials while the corpus often lacks the corresponding words of the target language, which makes machine translation powerless Besides, machine translation is not culturally sensitive. Human may never be able to program machines to understand and experience a particular culture. Different cultures have unique and different language systems, and machines do not have complexity to understand or recognize slang, jargon, puns and idioms. Therefore, their translation may not conform to cultural values and specific norms. This is also one of the challenges that the machine needs to overcome.[6] Artificial intelligence may have human abstract thinking ability in the future, but it is difficult to have image thinking ability including imagination and emotion. [7] Therefore, machine translation is often used in news, science and technology, patents, specifications and other text fields with the purpose of fact description, knowledge and information transmission. These words rarely involve emotional and cultural background. When translating expressive texts, the limitations of machine translation are exposed. The so-called expressive text refers to the text that pays attention to emotional expression and is full of imagination. Its main characteristics are subjectivity, emotion and imagination, such as novels, poetry, prose, art and so on. This kind of text attaches importance to the emotional expression of the author or character image, and uses a lot of metaphors, symbols and other expressions. Machine translation is difficult to catch up with artificial translation in this kind of text, it can only translate the main idea, lack of connotation and literary grace and it cannot have subjective feelings and rational analysis like human beings. In fact, it is not difficult to simulate the human brain, the difficulty is that it is impossible to learn from the rich social experience and life experience of excellent translators. In other words, machine translation lacks the personalization and creativity of human translation. It is this personalization and creativity that promote the development and evolution of language, and what machine translation can only output is mechanical "machine language".

3.The Irreplaceability of Artificial Translation

3.1 Translation is Constrained by Context

At present, machine translation can help people deal with language communication in people's daily life and work, such as clothing, food, housing and transportation, but there is a big gap from the "faithfulness, expressiveness and elegance" emphasized by high-level translation. Language itself is art，which pays more attention to artistry than functionality, and the discipline of art is difficult to quantify and unify. Sometimes it is regular, rigorous, logical and clear, and sometimes it is random, free and logical. If it is translated by machine, it is difficult to grasp this degree. Sometimes, machine translation cannot connect words with contextual meaning. In many languages, the same word may have multiple completely unrelated meanings. In this case, context will have a great impact on word meaning, and the understanding of word meaning depends largely on the meaning read from context. Only human beings can combine words with context, determine their true meaning, and creatively adjust and modify the language to obtain a complete and accurate translation. This is undoubtedly very difficult for machine translation. Artificial translation can get rid of the constraints of the source language and translate the translation in line with the grammar, sentence patterns and word habits of the target language. In the process of translation, translators can use their own knowledge reserves to analyze the differences between the source language and the target language in thinking mode, cultural characteristics, social background, customs and habits, so as to translate a more accurate translation. Artificial translation can also add, delete, domesticate, modify and polish the translation according to the style, make up for the lack of culture, try to maintain the thought, artistic conception and charm of the original text and the style of the source language. In addition, translators can also judge and consider the words with multiple meanings or easy to produce ambiguity according to the context, so as to make the translation more clear and more accurate and improve the quality of the translation.