HW-TSC Systems for WMT22 Very Low Resource Supervised MT Task
Shaojun Li, Yuanchang Luo, Daimeng Wei, Zongyao Li, Hengchao Shang, Xiaoyu Chen, Zhanglin Wu, Jinlong Yang, Zhiqiang Rao, Zhengzhe Yu, Yuhao Xie, Lizhi Lei, Hao Yang, Ying Qin
Abstract
This paper describes the submissions of Huawei translation services center (HW-TSC) to the WMT22 Very Low Resource Supervised MT task. We participate in all 6 supervised tracks including all combinations between Upper/Lower Sorbian (Hsb/Dsb) and German (De). Our systems are build on deep Transformer with a large filter size. We use multilingual transfer with German-Czech (De-Cs) and German-Polish (De-Pl) parallel data. We also utilize regularized dropout (R-Drop), back translation, fine-tuning and ensemble to improve the system performance. According to the official evaluation results on OCELoT, our supervised systems of all 6 language directions get the highest BLEU scores among all submissions. Our pre-trained multilingual model for unsupervised De2Dsb and Dsb2De translation also gain highest BLEU.- Anthology ID:
- 2022.wmt-1.107
- Volume:
- Proceedings of the Seventh Conference on Machine Translation (WMT)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1098–1103
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.107
- DOI:
- Cite (ACL):
- Shaojun Li, Yuanchang Luo, Daimeng Wei, Zongyao Li, Hengchao Shang, Xiaoyu Chen, Zhanglin Wu, Jinlong Yang, Zhiqiang Rao, Zhengzhe Yu, Yuhao Xie, Lizhi Lei, Hao Yang, and Ying Qin. 2022. HW-TSC Systems for WMT22 Very Low Resource Supervised MT Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1098–1103, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- HW-TSC Systems for WMT22 Very Low Resource Supervised MT Task (Li et al., WMT 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.wmt-1.107.pdf