Neural machine translation

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Neural machine translation (NMT) is an approach to machine translation that attempts to build and train a large neural network that reads a sentence and outputs a correct translation. Contrary to the traditional phrase-based machine translation system which is composed of different small sub-components that are tuned separately.

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An Empirical Study of Adequate Vision Span for Attention-Based Neural Machine Translation

Raphael Shu, Hideki Nakayama

http://arxiv.org/abs/1612.06043v4

Academic paper

Compression of Neural Machine Translation Models via Pruning

Abigail See, Minh-Thang Luong, Christopher D. Manning

http://arxiv.org/abs/1606.09274v1

Academic paper

Decoding-History-Based Adaptive Control of Attention for Neural Machine Translation

Junyang Lin, Shuming Ma, Qi Su, Xu Sun

http://arxiv.org/abs/1802.01812v1

Academic paper

English-Catalan Neural Machine Translation in the Biomedical Domain through the cascade approach

Marta R. Costa-jussà, Noe Casas, Maite Melero

http://arxiv.org/abs/1803.07139v1

Academic paper

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

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

http://arxiv.org/abs/1609.08144v2

Academic paper

Neural machine translation

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