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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]
The new translation engine was first enabled for eight languages: to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish in November 2016. [24] In March 2017, three additional languages were enabled: Russian, Hindi and Vietnamese along with Thai for which support was added later.
Users could then review and improve the automatic translation by clicking on the sentence and fixing a translation, or using Google's translation tools to help them translate by clicking the "Show toolkit" button. Users could view translations previously entered by other users in the "Translation search results" tab or use the "Dictionary" tab ...
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.
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.
Anusaaraka is an English to Hindi language accessing (translation) software, which employs algorithms derived from Pāṇini's Ashtadhyayi (Grammar rules). [1] [2] The software is being developed by the Chinmaya International Foundation (CIF) [3] at the International Institute of Information Technology, Hyderabad (IIIT-H) and the University of Hyderabad Department of Sanskrit Studies. [4]
Apertium is a transfer-based machine translation system, which uses finite state transducers for all of its lexical transformations, and Constraint Grammar taggers as well as hidden Markov models or Perceptrons for part-of-speech tagging / word category disambiguation. [2]
The accuracy of Google Translate continues to improve, and in many cases approaches the accuracy of human translation; Use of non-English sources can help counter systemic bias on Wikipedia, which skews to Anglocentric and Eurocentric perspectives; Cons. Accuracy may not be sufficient for all uses, and human translation is still more accurate
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