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2. Google Translate - Wikipedia

   en.wikipedia.org/wiki/Google_Translate

   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] The input text had to be translated into English first ...

3. Google Neural Machine Translation - Wikipedia

   en.wikipedia.org/wiki/Google_Neural_Machine...

   v. t. e. 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. [1][2][3][4] The neural network consisted of two main blocks, an encoder and a decoder, both of LSTM ...

4. Microsoft Translator - Wikipedia

   en.wikipedia.org/wiki/Microsoft_Translator

   Bing Microsoft Translator (previously Live Search Translator, Windows Live Translator, and Bing Translator) [ 19 ] is a user-facing translation portal provided by Microsoft as part of its Bing services to translate texts or entire web pages into different languages. All translation pairs are powered by the Microsoft Translator, a neural machine ...

5. Machine translation - Wikipedia

   en.wikipedia.org/wiki/Machine_translation

   Kural translations by language. v. t. e. Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical.

6. Rule-based machine translation - Wikipedia

   en.wikipedia.org/wiki/Rule-based_machine_translation

   Appearance. Rule-based machine translation (RBMT; "Classical Approach" of MT) is machine translation systems based on linguistic information about source and target languages basically retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each ...

7. BERT (language model) - Wikipedia

   en.wikipedia.org/wiki/BERT_(language_model)

   BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1][2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture. It was notable for its dramatic improvement over ...