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, 2016, arXiv

one deep sequence to sequence model per language pair, in production

Read it

English

12 sections
0 figures
0 equations
45 references
cited by 3 here
the publisher's page

1Introduction
2Related Work
3Model Architecture
4Segmentation Approaches
5Training Criteria
6Quantizable Model and Quantized Inference
7Decoder
8Experiments and Results
9Conclusion
Acknowledgments

Its place here

citesDeep Residual Learning for Image Recognition
citesSequence to Sequence Learning with Neural Networks
cited byBERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
cited byIn-Datacenter Performance Analysis of a Tensor Processing Unit
cited byAttention Is All You Need

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

Read it

Contents

Its place here