Google launched its public translation service in 2006, supporting only a small number of language pairs. Its core machine translation service, Google Translate, is one of the most used free MT tools worldwide. Google, one of the leading MT providers today, has had a critical impact on making MT a viable productivity tool for both personal and business use. How best to implement machine translation into translation workflows? How much can you trust the translation produced by a machine? To what extent does MT properly convey the original meaning of the content? In other words, is it accurate? However, there are still some questions swirling around the use of machine translation software. It seemed to solve all the problems posed previously-instant translation done for free. Machine translation (MT), which automatically translates non-matching pairs without the need for a professional translator, has taken translation capabilities even further.Īlso referred to as automatic translation, MT quickly became available to anyone thanks to the internet, and many technology vendors began to offer machine translation services for free. Nonetheless, even with heavily involving a CAT tool, matching pairs had to be reviewed in context, and non-matching pairs still needed translation. Different computer-assisted translation (CAT) tools were then developed, which significantly improved productivity. How does Amazon Translate compare to Google Translate?įrom statistical models to deep learning in translation technologyĬomputers brought enormous improvements in translation with their ability to store already translated sentences and match them with new texts to translate.

Does Google Translate have any major competitors?.How do you assess Google Translate’s performance?.

How has Google Translate’s accuracy improved over time?.

Does Google Translate use English as an intermediary step?.

What technology does Google Translate use in the backend?.

From statistical models to deep learning in translation technology.

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