The Path to Continuous Domain Adaptation Improvements by HW-TSC for the WMT23 Biomedical Translation Shared Task

Zhanglin Wu, Daimeng Wei, Zongyao Li, Zhengzhe Yu, Shaojun Li, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Yuhao Xie, Lizhi Lei, Hao Yang, Yanfei Jiang

Abstract: This paper presents the domain adaptation methods adopted by Huawei Translation Service Center (HW-TSC) to train the neural machine translation (NMT) system on the English↔German (en↔de) language pair of the WMT23 biomedical translation task. Our NMT system is built on deep Transformer with larger parameter sizes. Based on the biomedical NMT system trained last year, we leverage Curriculum Learning, Data Diversification, Forward translation, Back translation, and Transductive Ensemble Learning to further improve system performance. Overall, we believe our submission can achieve highly competitive result in the official final evaluation.