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Google Translate is a web-based free-to-use translation service developed by Google in April 2006. [12] It translates multiple forms of texts and media such as words, phrases and webpages. Originally, Google Translate was released as a statistical machine translation (SMT) service. [ 12 ]
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 .
This is a list of the most translated literary works (including novels, plays, series, collections of poems or short stories, and essays and other forms of literary non-fiction) sorted by the number of languages into which they have been translated.
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 ...
When the online service was first introduced, the head of Yandex.Translate, Alexei Baitin, stated that although machine translation cannot be compared to a literary text, the translations produced by the system can provide a convenient option for understanding the general meaning of the text in a foreign language.
Babel Fish was a free Web-based machine translation service by Yahoo!. In May 2012 it was replaced by Bing Translator (now Microsoft Translator ), to which queries were redirected. [ 1 ] Although Yahoo! has transitioned its Babel Fish translation services to Bing Translator, it did not sell its translation application to Microsoft outright.
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.
GNMT improved on the quality of translation by applying an example-based (EBMT) machine translation method in which the system learns from millions of examples of language translation. [2] GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. [ 2 ]