Neural machine translation

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]

  1. ^ a b c Cite error: The named reference Koehn2020 was invoked but never defined (see the help page).
  2. ^ Cite error: The named reference Stahlberg2020 was invoked but never defined (see the help page).
  3. ^ Cite error: The named reference Popel2020 was invoked but never defined (see the help page).
  4. ^ Cite error: The named reference Haddow2022 was invoked but never defined (see the help page).
  5. ^ a b Cite error: The named reference Poibeau2022 was invoked but never defined (see the help page).

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