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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.
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
Google Translate previously first translated the source language into English and then translated the English into the target language rather than translating directly from one language to another. [11] A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne-based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL. It initially offered translations between seven European languages and has since gradually expanded to support 33 languages.
In addition, integration with machine translation has been disabled for all users. [1] Due to a configuration error, [2] between at least 11 December 2015 [3] and 26 July 2016, [4] this tool was using machine translation from the source language to English. The user was then expected to check and fix the translation before publication.
Demonstration of the languages which are used in the process of translating using a bridge language. Interlingual machine translation is one of the classic approaches to machine translation. In this approach, the source language, i.e. the text to be translated is transformed into an interlingua, i.e., an abstract language-independent ...
Previously, machine translation was based on "the meaning of the text" model: take any language, translate the words in the universal language of the senses, and then translate these meanings in the words of another language – and obtain the translated text. This model prevailed in the 1970s-1980s and automated in the 1990s.