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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]
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 .
Microsoft Translator or Bing Translator is a multilingual machine translation cloud service provided by Microsoft.Microsoft Translator is a part of Microsoft Cognitive Services [1] and integrated across multiple consumer, developer, and enterprise products, including Bing, Microsoft Office, SharePoint, Microsoft Edge, Microsoft Lync, Yammer, Skype Translator, Visual Studio, and Microsoft ...
Immediately after the launch of the translator in beta mode in the spring of 2010, it was only available in three languages — English, Russian and Ukrainian, with a limit of 10,000 characters. [2] Yandex.Translate has some languages that are missing from Google Translate, such as Russia's national minority languages.
Google Translator Toolkit by default used Google Translate to automatically pre-translate uploaded documents which translators could then improve. Google Inc released Google Translator Toolkit on June 8, 2009. [2] This product was expected to be named Google Translation Center, as had been announced in August 2008.
Google Neural Machine Translation (GNMT) was a neural machine translation (NMT) system developed by Google and introduced in November 2016 that used an artificial neural network to increase fluency and accuracy in Google Translate.
Historically, ProMT systems used rule-based machine translation (RBMT) technology. [4] In 2011 a hybrid approach which combined rule-based and statistical MT was implemented.
Translator computing facilitates the conversion between these abstraction levels. [3] Overall, translator computing plays a crucial role in bridging the gap between software and hardware implementations, enabling developers to leverage the strengths of each platform and optimize performance, power efficiency, and other metrics according to the ...