Abstract
This paper describes Huawei’s neural machine translation systems for the WMT 2019 biomedical translation shared task. We trained and fine-tuned our systems on a combination of out-of-domain and in-domain parallel corpora for six translation directions covering English–Chinese, English–French and English–German language pairs. Our submitted systems achieve the best BLEU scores on English–French and English–German language pairs according to the official evaluation results. In the English–Chinese translation task, our systems are in the second place. The enhanced performance is attributed to more in-domain training and more sophisticated models developed. Development of translation models and transfer learning (or domain adaptation) methods has significantly contributed to the progress of the task.- Anthology ID:
- W19-5420
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 164–168
- Language:
- URL:
- https://aclanthology.org/W19-5420
- DOI:
- 10.18653/v1/W19-5420
- Cite (ACL):
- Wei Peng, Jianfeng Liu, Liangyou Li, and Qun Liu. 2019. Huawei’s NMT Systems for the WMT 2019 Biomedical Translation Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 164–168, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Huawei’s NMT Systems for the WMT 2019 Biomedical Translation Task (Peng et al., WMT 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-5420.pdf