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  1. Natural language processing - Wikipedia

    en.wikipedia.org › wiki › Natural_language_processing

    For instance, the term neural machine translation (NMT) emphasizes the fact that deep learning-based approaches to machine translation directly learn sequence-to-sequence transformations, obviating the need for intermediate steps such as word alignment and language modeling that was used in statistical machine translation (SMT). Latest works ...

  2. Google Brain - Wikipedia

    en.wikipedia.org › wiki › Google_Brain

    The Google Brain team contributed to the Google Translate project by employing a new deep learning system that combines artificial neural networks with vast databases of multilingual texts. In September 2016, Google Neural Machine Translation (GNMT) was launched, an end-to-end learning framework, able to learn from a large number of examples.

  3. Deep learning - Wikipedia

    en.wikipedia.org › wiki › Deep_learning

    Neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. As of 2017, neural networks typically have a few thousand to a few million units and millions of connections.

  4. Translation - Wikipedia

    en.wikipedia.org › wiki › Translation

    Translation is the communication of the meaning of a source-language text by means of an equivalent target-language text. The English language draws a terminological distinction (which does not exist in every language) between translating (a written text) and interpreting (oral or signed communication between users of different languages); under this distinction, translation can begin only ...

  5. Wikizero - Neural machine translation

    www.wikizero.com › en › Neural_machine_translation

    Neural machine translation From Wikipedia the free encyclopedia Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

  6. Yandex.Translate - Wikipedia

    en.wikipedia.org › wiki › Yandex

    In September 2017, Yandex.Translate switched to a hybrid approach incorporating both statistical machine translation and neural machine translation models. [5] The translation page first appeared in 2009 [ citation needed ] , utilizing PROMT , and was also built into Yandex Browser itself, to assist in translation for websites.

  7. Self-Supervised Neural Machine Translation

    www.aclweb.org › anthology › P19-1178

    stest2014 using English and French Wikipedia data for training. 1 Introduction Neural machine translation (NMT) has brought major improvements in translation quality (Cho et al.,2014;Bahdanau et al.,2014;Vaswani et al., 2017). Until recently, these relied on the avail-ability of high-quality parallel corpora. As such

  8. Neural Machine Translation - ResearchGate

    www.researchgate.net › publication › 341875495

    End-to-end neural machine translation has overtaken statistical machine translation in terms of translation quality for some language pairs, specially those with a large amount of parallel data ...

  9. Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara Allahsera Auguste Tapo 1;, Bakary Coulibaly 2, Sébastien Diarra , Christopher Homan , Julia Kreutzer3, Sarah Luger4, Arthur Nagashima 1, Marcos Zampieri , Michael Leventhal2 1Rochester Institute of Technology

  10. Wikipedia data we use, we also use scored WikiMa-trix data for one of the comparisons (Section3.2). 3 Self-Supervised Neural Machine Translation (SSNMT) SSNMT is a joint data selection and training frame-work for machine translation, introduced inRuiter et al.(2019). SSNMT enables learning NMT from comparable rather than parallel data, where com-

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