Baidu Neural Machine Translation Systems for WMT19

Meng Sun, Bojian Jiang, Hao Xiong, Zhongjun He, Hua Wu, Haifeng Wang


Abstract
In this paper we introduce the systems Baidu submitted for the WMT19 shared task on Chinese<->English news translation. Our systems are based on the Transformer architecture with some effective improvements. Data selection, back translation, data augmentation, knowledge distillation, domain adaptation, model ensemble and re-ranking are employed and proven effective in our experiments. Our Chinese->English system achieved the highest case-sensitive BLEU score among all constrained submissions, and our English->Chinese system ranked the second in all submissions.
Anthology ID:
W19-5341
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
374–381
Language:
URL:
https://www.aclweb.org/anthology/W19-5341
DOI:
10.18653/v1/W19-5341
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-5341.pdf