HW-TSC Translation Systems for the WMT22 Biomedical Translation Task

Zhanglin Wu, Jinlong Yang, Zhiqiang Rao, Zhengzhe Yu, Daimeng Wei, Xiaoyu Chen, Zongyao Li, Hengchao Shang, Shaojun Li, Ming Zhu, Yuanchang Luo, Yuhao Xie, Miaomiao Ma, Ting Zhu, Lizhi Lei, Song Peng, Hao Yang, Ying Qin

Abstract
This paper describes the translation systems trained by Huawei translation services center (HW-TSC) for the WMT22 biomedical translation task in five language pairs: English↔German (en↔de), English↔French (en↔fr), English↔Chinese (en↔zh), English↔Russian (en↔ru) and Spanish→English (es→en). Our primary systems are built on deep Transformer with a large filter size. We also utilize R-Drop, data diversification, forward translation, back translation, data selection, finetuning and ensemble to improve the system performance. According to the official evaluation results in OCELoT or CodaLab, our unconstrained systems in en→de, de→en, en→fr, fr→en, en→zh and es→en (clinical terminology sub-track) get the highest BLEU scores among all submissions for the WMT22 biomedical translation task.
Anthology ID:
2022.wmt-1.88
Volume:
Proceedings of the Seventh Conference on Machine Translation (WMT)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Venue:
WMT
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Publisher:
Association for Computational Linguistics
Note:
Pages:
936–942
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URL:
https://aclanthology.org/2022.wmt-1.88
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Cite (ACL):
Zhanglin Wu, Jinlong Yang, Zhiqiang Rao, Zhengzhe Yu, Daimeng Wei, Xiaoyu Chen, Zongyao Li, Hengchao Shang, Shaojun Li, Ming Zhu, Yuanchang Luo, Yuhao Xie, Miaomiao Ma, Ting Zhu, Lizhi Lei, Song Peng, Hao Yang, and Ying Qin. 2022. HW-TSC Translation Systems for the WMT22 Biomedical Translation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 936–942, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
HW-TSC Translation Systems for the WMT22 Biomedical Translation Task (Wu et al., WMT 2022)
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