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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. [11] A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
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Exfoliation methods used in Canada, 2011. Shown: top right, a bath sponge made of plastic mesh; lower right, a brush with a pumice stone on one side and a natural bristle brush on the other side, for foot exfoliation; lower left, a mud mask package for facial exfoliation; top left, a jar of perfumed body scrub to be used while bathing.
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.
To use Google Translator Toolkit first, users uploaded a file from their desktop or entered a URL of a web page or Wikipedia article that they want to translate. Google Translator Toolkit automatically 'pretranslated' the document. It divided the document into segments, usually sentences, headers, or bullets.
The reception of DeepL Translator has been generally positive. TechCrunch appreciates it for the accuracy of its translations and stating that it was more accurate and nuanced than Google Translate. [3] Le Monde thank its developers for translating French text into more "French-sounding" expressions. [38]
Previously, machine translation was based on "the meaning of the text" model: take any language, translate the words in the universal language of the senses, and then translate these meanings in the words of another language – and obtain the translated text. This model prevailed in the 1970s-1980s and automated in the 1990s.