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Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages.

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Origins

The idea of using digital computers for translation of natural languages was proposed as early as 1947 by England's A. D. Booth[5] and Warren Weaver at Rockefeller Foundation in the same year. "The memorandum written by Warren Weaver in 1949 is perhaps the single most influential publication in the earliest days of machine translation."[6][7] Others followed. A demonstration was made in 1954 on the APEXC machine at Birkbeck College (University of London) of a rudimentary translation of English into French. Several papers on the topic were published at the time, and even articles in popular journals (for example an article by Cleave and Zacharov in the September 1955 issue of Wireless World). A similar application, also pioneered at Birkbeck College at the time, was reading and composing Braille texts by computer.

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Rule-based

Main article: Rule-based machine translation

The rule-based machine translation approach was used mostly in the creation of dictionaries and grammar programs. Its biggest downfall was that everything had to be made explicit: orthographical variation and erroneous input must be made part of the source language analyser in order to cope with it, and lexical selection rules must be written for all instances of ambiguity.

Transfer-based machine translation

Main article: Transfer-based machine translation

Transfer-based machine translation was similar to interlingual machine translation in that it created a translation from an intermediate representation that simulated the meaning of the original sentence. Unlike interlingual MT, it depended partially on the language pair involved in the translation.

Interlingual

Main article: Interlingual machine translation

Interlingual machine translation was one instance of rule-based machine-translation approaches. In this approach, the source language, i.e. the text to be translated, was transformed into an interlingual language, i.e. a "language neutral" representation that is independent of any language. The target language was then generated out of the interlingua. The only interlingual machine translation system that was made operational at the commercial level was the KANT system (Nyberg and Mitamura, 1992), which was designed to translate Caterpillar Technical English (CTE) into other languages.

Dictionary-based

Main article: Dictionary-based machine translation

Machine translation used a method based on dictionary entries, which means that the words were translated as they are by a dictionary.

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Machine translation and signed languages

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Machine translation and signed languages

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Main article: Machine translation of sign languages

In the early 2000s, options for machine translation between spoken and signed languages were severely limited. It was a common belief that deaf individuals could use traditional translators. However, stress, intonation, pitch, and timing are conveyed much differently in spoken languages compared to signed languages. Therefore, a deaf individual may misinterpret or become confused about the meaning of written text that is based on a spoken language.[74]

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Machine Translation (MT) is a subfield of computational linguistics that focuses on the automated translation of text or speech from one language to another, having three main types: Rule-Based, Statistical, and Neural Machine Translation.

Rule-Based Machine Translation (RBMT) relies on linguistic rules and dictionaries, Statistical Machine Translation (SMT) uses statistical models based on bilingual text corpora, and Neural Machine Translation (NMT) utilizes deep learning techniques and neural networks.

Machine Translation approaches include Direct, Transfer, and Interlingua, primarily used in rule-based machine translation systems.

Practical applications of machine translation include information retrieval, e-commerce, social media, education, government and legal, and customer support; however, it has limitations such as translation errors, lack of cultural nuance, and difficulty with domain-specific language.

Machine Translation (MT) is an automated process, while Computer-Assisted Translation (CAT) is a set of software tools used to assist human translators in their work, with both offering different advantages and disadvantages in terms of quality, speed, cost, and application.