Neural Machine Translation (NMT) Algorithm

From GM-RKB
Jump to navigation Jump to search

A Neural Machine Translation (NMT) Algorithm is a data-driven MT algorithm that uses a neural NLP algorithm.



References

2018

2018b

2017a

2017b

  • (Monroe, 2017) ⇒ Don Monroe. (2017). “Deep Learning Takes on Translation.” In: Communications of the ACM Journal, 60(6). doi:10.1145/3077229
    • QUOTE: … Most implementations of translation employ two neural networks. The first, called the encoder, processes input text from one language to create an evolving fixed-length vector representation of the evolving input. A second "decoder" network monitors this vector to produce text in a different language. Typically, the encoder and decoder are trained as a pair for each choice of source and target language.

      An additional critical element is the use of "attention," which Cho said was "motivated from human translation." As translation proceeds, based on what has been translated so far, this attention mechanism selects the most useful part of the text to translate next.

2016

2016

2014b

2014a