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Google Neural Machine Translation (GNMT) was a neural machine translation (NMT) system developed by Google and introduced in November 2016 that used an artificial neural network to increase fluency and accuracy in Google Translate.
Pros and cons. Pros. 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.
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Does Google Translate use neural machine translation?
How accurate is Google Translate?
How does Google Translate work?
What is Google neural machine translation (GNMT)?
While not instantaneous like its machine counterparts such as Google Translate and Babel Fish (now defunct), as of 2010 web-based human translation has been gaining popularity by providing relatively fast, accurate translation of business communications.
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Computer-aided translation (CAT), also referred to as computer-assisted translation or computer-aided human translation (CAHT), is the use of software, also known as a translator, to assist a human translator in the translation process.
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
This table lists all two-letter codes (set 1), one per language for ISO 639 macrolanguage, and some of the three-letter codes of the other sets, formerly parts 2 and 3. Entries in the Scope column distinguish: Individual language. Collections of related languages. Macrolanguages.
