Abstract
This paper describes LISN’s submissions to two shared tasks at WMT’21. For the biomedical translation task, we have developed resource-heavy systems for the English-French language pair, using both out-of-domain and in-domain corpora. The target genre for this task (scientific abstracts) corresponds to texts that often have a standardized structure. Our systems attempt to take this structure into account using a hierarchical system of sentence-level tags. Translation systems were also prepared for the News task for the French-German language pair. The challenge was to perform unsupervised adaptation to the target domain (financial news). For this, we explored the potential of retrieval-based strategies, where sentences that are similar to test instances are used to prime the decoder.- Anthology ID:
- 2021.wmt-1.22
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 232–242
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.22
- DOI:
- Cite (ACL):
- Jitao Xu, Minh Quang Pham, Sadaf Abdul Rauf, and François Yvon. 2021. LISN @ WMT 2021. In Proceedings of the Sixth Conference on Machine Translation, pages 232–242, Online. Association for Computational Linguistics.
- Cite (Informal):
- LISN @ WMT 2021 (Xu et al., WMT 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.wmt-1.22.pdf