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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 ...
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.
It was launched as DeepL Translator on 28 August 2017 and offered translations between English, German, French, Spanish, Italian, Polish and Dutch. [ 18 ] [ 19 ] [ 20 ] [ 7 ] At its launch, it claimed to have surpassed its competitors in blind tests and BLEU scores, including Google Translate , Amazon Translate, Microsoft Translator and ...
Linguee is an online bilingual concordance that provides an online dictionary for a number of language pairs, including many bilingual sentence pairs. As a translation aid, Linguee differs from machine translation services like Babel Fish, and is more similar in function to a translation memory.
As of July 2019, Microsoft Translator supports over 65 languages and can translate video calls between English, French, German, Chinese (Mandarin), Italian, and Spanish. In 2010, Google announced that it was developing a translator.
The English-to-German translation model was trained on the 2014 WMT English-German dataset consisting of nearly 4.5 million sentences derived from TED Talks and high-quality news articles. A separate translation model was trained on the much larger 2014 WMT English-French dataset, consisting of 36 million sentences.
Users could then review and improve the automatic translation by clicking on the sentence and fixing a translation, or using Google's translation tools to help them translate by clicking the "Show toolkit" button. Users could view translations previously entered by other users in the "Translation search results" tab or use the "Dictionary" tab ...
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