Neural machine translation
Approach to machine translation using artificial neural networks / From Wikipedia, the free encyclopedia
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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.
It is the dominant approach today[1]: 293 [2]: 1 and can produce translations that rival human translations when translating between high-resource languages under specific conditions.[3] However, there still remain challenges, especially with languages where less high-quality data is available,[4][5][1]: 293 and with domain shift between the data a system was trained on and the texts it is supposed to translate.[1]: 293 NMT systems also tend to produce fairly literal translations.[5]