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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] The input text had to be translated into English first ...
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 ...
Yandex Translate (Russian: Яндекс Переводчик, romanized: Yandeks Perevodchik) is a web service provided by Yandex, intended for the translation of web pages into another language. The service uses a self-learning statistical machine translation, [3] developed by Yandex. [4] The system constructs the dictionary of single-word ...
The demo showed how Google’s Translate can automatically listen to speech and translate it in real-time, displaying the translated text for the wearer to see and read with ease.
Speech Recognition & Synthesis. Speech Recognition & Synthesis, formerly known as Speech Services, [3] is a screen reader application developed by Google for its Android operating system. It powers applications to read aloud (speak) the text on the screen, with support for many languages. Text-to-Speech may be used by apps such as Google Play ...
Georgetown–IBM experiment. The Georgetown–IBM experiment was an influential demonstration of machine translation, which was performed on January 7, 1954. Developed jointly by the Georgetown University and IBM, the experiment involved completely automatic translation of more than sixty Russian sentences into English. [1][2]
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.
Languages features comparison. 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.