DiDi’s Machine Translation System for WMT2020

Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, Kevin Knight


Abstract
This paper describes the DiDi AI Labs’ submission to the WMT2020 news translation shared task. We participate in the translation direction of Chinese->English. In this direction, we use the Transformer as our baseline model and integrate several techniques for model enhancement, including data filtering, data selection, back-translation, fine-tuning, model ensembling, and re-ranking. As a result, our submission achieves a BLEU score of 36.6 in Chinese->English.
Anthology ID:
2020.wmt-1.7
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
105–112
Language:
URL:
https://aclanthology.org/2020.wmt-1.7
DOI:
Bibkey:
Cite (ACL):
Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, and Kevin Knight. 2020. DiDi’s Machine Translation System for WMT2020. In Proceedings of the Fifth Conference on Machine Translation, pages 105–112, Online. Association for Computational Linguistics.
Cite (Informal):
DiDi’s Machine Translation System for WMT2020 (Chen et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.7.pdf
Video:
 https://slideslive.com/38939543