Neural Machine Translation (NMT) System

A Neural Machine Translation (NMT) System is a statistical machine translation system that is a neural NLP system.

• Context:
  • It can solve a Machine Learning Translation Task by implementing a Machine Learning Translation Algorithm.
• Example(s):
  • a seq2seq-based NMT System.
  • a Google's NMT System (Wu et al., 2016).
  • a Sennrich-Haddow-Birch Rare Words Neural Machine Translation System (Sennrich et al.,2016).
  • a Bahdanau-Cho-Bengio Neural Machine Translation System (Bahdanau et al.,2015).
  • …
• Counter-Example(s):
  • a Word Segmentation System,
  • a OOV Detection System,
  • a Grammatical Error Correction System.
• See: Neural seq2seq System, Neural Text Generation System, Natural Language Processing System, Neural Encoder-Decoder System.

---

---

References

2016a

• (Wu et al., 2016) ⇒ Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean. (2016). “Google's Neural Machine Translation System: Bridging the Gap Between Human and Machine Translation.” arXiv preprint arXiv:1609.08144
  • QUOTE: Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems. Unfortunately, NMT systems are known to be computationally expensive both in training and in translation inference. Also, most NMT systems have difficulty with rare words. .

2016b

• (Sennrich et al., 2016) ⇒ Rico Sennrich, Barry Haddow, and Alexandra Birch. (2016). "Neural Machine Translation of Rare Words with Subword Units". In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016).

2015

• (Bahdanau et al., 2015) ⇒ Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. (2015). “Neural Machine Translation by Jointly Learning to Align and Translate.” In: Proceedings of the Third International Conference on Learning Representations, (ICLR-2015).

---