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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]
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. A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
Machine translation (MT) is a process whereby a computer program analyzes a source text and, in principle, produces a target text without human intervention. In reality, however, machine translation typically does involve human intervention, in the form of pre-editing and post-editing. [97]
Google Dictionary is an online dictionary service of Google that can be accessed with the " define " operator and other similar phrases [note 1] in Google Search. [2] It is also available in Google Translate and as a Google Chrome extension. The dictionary content is licensed from Oxford University Press 's Oxford Languages. [3]
Machine translation is use of either rule-based or probabilistic (i.e. statistical and, most recently, neural network-based) machine learning approaches to translation of text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages.
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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.
Statistical machine translation. Statistical machine translation ( SMT) was a machine translation approach, that superseded the previous, rule-based approach because it required explicit description of each and every linguistic rule, which was costly, and which often did not generalize to other languages. Since 2003, the statistical approach ...
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