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  2. DeepL Translator - Wikipedia

    en.wikipedia.org/wiki/DeepL_Translator

    DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne-based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL .

  3. Google Translate - Wikipedia

    en.wikipedia.org/wiki/Google_Translate

    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]

  4. Naver Papago - Wikipedia

    en.wikipedia.org/wiki/Naver_Papago

    Image Translation: The portion of a photo in a gallery or the characters in a newly photographed picture is specified and translated into text. It is available in six languages: Korean , English , Japanese , Chinese , Vietnamese , and Thai .

  5. Comparison of machine translation applications - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_machine...

    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.

  6. Here’s Exactly How Much Protein You Need To Build 1 ... - AOL

    www.aol.com/exactly-much-protein-build-1...

    To increase muscle size (called hypertrophy), your body needs to make more muscle protein than it breaks down over time. Eating enough protein is one way to do this. Eating enough protein is one ...

  7. Comparison of computer-assisted translation tools - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_computer...

    A number of computer-assisted translation software and websites exists for various platforms and access types. According to a 2006 survey undertaken by Imperial College of 874 translation professionals from 54 countries, primary tool usage was reported as follows: Trados (35%), Wordfast (17%), Déjà Vu (16%), SDL Trados 2006 (15%), SDLX (4%), STAR Transit [fr; sv] (3%), OmegaT (3%), others (7%).

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