The introduction and brief history about machine translation
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Machine translation, also known as automatic translation, is the process of using a computer 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 has played an increasingly important role in promoting political, economic, and cultural exchanges.
Introduction to machine translation
The development of machine translation technology has been closely following the development of disciplines such as computer technology, information theory, and linguistics. From the early dictionary matching, to the rule translation of dictionaries combined with the knowledge of linguistic experts, 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 has gradually stepped out of the ivory tower. Started to provide real-time and convenient translation services for ordinary users.
Brief History
development route
The research history of machine translation can be traced back to the 1930s and 1940s. In the early 1930s, French scientist G.B. Arcuni proposed the idea of using machines for translation. In 1933, the Soviet inventor П.П. Troyansky designed a machine to translate one language into another, and registered his invention on September 5 of the same year; however, due to the technical level of the 1930s It's still very low, and his translator hasn't been made. In 1946, the first modern electronic computer ENIAC was born. Shortly afterwards, when discussing the application range of electronic computers, the pioneer of information theory, American scientist W. Weaver and British engineer AD Booth, in 1947 proposed the use of computers for automatic language translation. idea. In 1949, W. Weaver published "Translation Memorandum", formally proposing the idea of machine translation. After sixty years of ups and downs, machine translation has experienced a tortuous and long development path. The academic circles generally divide it into the following four stages，
Pioneering period
(1947-1964)
In 1954, Georgetown University in the United States, in collaboration with IBM, used the IBM-701 computer to complete the English-Russian machine translation experiment for the first time, demonstrating the feasibility of machine translation to the public and the scientific community, thus opening up machine translation. The prologue of the research.
It is not too late for China to start this research. As early as 1956, the country included this research in the national scientific work development plan. The title of the project was "machine translation, the construction of natural language translation rules, and the mathematical theory of natural language". .
From the 1950s to the first half of the 1960s, machine translation research has shown an upward trend. The two superpowers of the United States and the former Soviet Union have provided a large amount of financial support for machine translation projects for military, political and economic purposes. European countries have also paid considerable attention to machine translation research due to geopolitical and economic needs. , Machine translation has a craze for a while. Although machine translation has just been in its pioneering stage in this period, it has entered an optimistic and prosperous period.
Frustration
(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), which began a two-year comprehensive investigation, analysis and testing.
In November 1966, the committee published a report entitled "Language and Machines" (ALPAC report for short), which completely denied the feasibility of machine translation and recommended that funding support for machine translation projects should be stopped. The publication of this report gave the booming machine translation a blow, and machine translation research has fallen into a deadlock that is almost stagnant. Machine translation has entered a period of depression.
Recovery period
(1975-1989)
After entering the 1970s, with the development of science and technology and the increasing frequency of scientific and technological information exchanges between countries, the language barriers between countries have become more serious. The traditional manual operation methods are far from meeting the needs, and computers are urgently needed. Engaged in translation work. At the same time, the development of computer science and linguistics research, especially the substantial improvement of computer hardware technology and the application of artificial intelligence in natural language processing, has promoted the recovery of machine translation research from the technical level, and machine translation projects have begun to develop. Various practical and experimental systems have been launched successively, such as Weinder system, EURPOTRA multilingual translation system, TAUM-METEO system, etc.
New era
(1990 to present)
With the widespread application of the Internet, the acceleration of the process of world economic integration and the increasing frequency of international social exchanges, traditional manual methods are far from meeting the rapidly growing demand for translation. People’s demand for machine translation has increased unprecedentedly. Translation has ushered in a new development opportunity. International conferences on machine translation research are held frequently, and a series of machine translation software have been launched. Driven by market demand, commercial machine translation systems have entered the practical stage, entered the market, and came to users.
Since the beginning of 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 established machine translation research groups and developed machine translation systems based on Internet big data, so that machine translation is truly practical. In recent years, with the progress of deep learning, machine translation technology has been further developed, which has promoted the rapid improvement of translation quality, and the translation in spoken language and other fields has become more authentic and smooth.
Translation process
The entire machine translation process can be divided into three stages: original source analysis, original source translation conversion, and translation generation. In a specific machine translation system, according to the purpose and requirements of different schemes, the original translation conversion stage and the original analysis stage can be combined, and the translation generation stage can be independent to establish an independent generation system for related analysis. In such a system, the characteristics of the target language should be considered when analyzing the original language, but the characteristics of the original language should not be considered when generating the target language. When studying the translation of multiple languages to one language, it is advisable to use such a correlation analysis to generate an independent system. It is also possible to separate the original source analysis stage and combine the original translation conversion stage with the translation generation stage to establish an independent analysis related generation system. In such a system, the characteristics of the target language are not considered in the analysis of the original language, but the characteristics of the original language should be considered when the target language is generated. When studying the translation of one language to multiple languages, such independent analysis is appropriate Related generation system. It is also possible to separate the original source analysis, original source translation conversion and translation generation separately, and establish an independent analysis and independent generation system. In such a system, the characteristics of the target language are not considered when analyzing the original language, and the characteristics of the original language are not considered when generating the target language. The difference between the original language and the target language is resolved through the conversion of the original language. When studying the translation of multiple languages to multiple languages, it is appropriate to adopt such an independent analysis and independent generation system.
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