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
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 374–381
- Language:
- URL:
- https://aclanthology.org/W19-5341
- DOI:
- 10.18653/v1/W19-5341
- Cite (ACL):
- Meng Sun, Bojian Jiang, Hao Xiong, Zhongjun He, Hua Wu, and Haifeng Wang. 2019. Baidu Neural Machine Translation Systems for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 374–381, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Baidu Neural Machine Translation Systems for WMT19 (Sun et al., WMT 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W19-5341.pdf
- Data
- WMT 2018