Abstract
This paper introduces WeChat’s participation in WMT 2022 shared biomedical translationtask on Chinese→English. Our systems are based on the Transformer(Vaswani et al., 2017),and use several different Transformer structures to improve the quality of translation. In our experiments, we employ data filtering, data generation, several variants of Transformer,fine-tuning and model ensemble. Our Chinese→English system, named Summer, achieves the highest BLEU score among all submissions.- Anthology ID:
- 2022.wmt-1.85
- 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:
- 920–924
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.85
- DOI:
- Cite (ACL):
- Ernan Li, Fandong Meng, and Jie Zhou. 2022. Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 920–924, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task (Li et al., WMT 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.wmt-1.85.pdf