Ten years ago, Google announced the launch of Google Translate, together with the use of Phrase-Based Machine Translation as the key algorithm behind this service. Since then, rapid advances in machine intelligence have improved our speech recognition and image recognition capabilities, but improving machine translation remains a challenging goal.

 

Today Google announced the Google Neural Machine Translation system (GNMT), which utilizes state-of-the-art training techniques to achieve the largest improvements to date for machine translation quality. Google’s full research results are described in a new technical report that Google is releasing today: “Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation”.

 

 

Image post 17-01-2017 GTranslate

 

Machine translation is by no means solved. GNMT can still make significant errors that a human translator would never make, like dropping words and mistranslating proper names or rare terms, and translating sentences in isolation rather than considering the context of the paragraph or page. There is still a lot of work that Google can do to serve users better. However, GNMT represents a significant milestone.

 

 

 

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