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-ofdomain 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.
https://hal.archives-ouvertes.fr/hal-03430610 Contributor : François YvonConnect in order to contact the contributor Submitted on : Friday, November 19, 2021 - 6:01:39 PM Last modification on : Monday, December 13, 2021 - 9:17:34 AM Long-term archiving on: : Sunday, February 20, 2022 - 6:09:36 PM
Jitao Xu, Sadaf Abdul Rauf, Minh Quang Pham, François yvon. LISN @ WMT 2021. 6th Conference on Statistical Machine Translation, Association for Computational Linguistics, Nov 2021, Punta Cuna, Dominica. ⟨hal-03430610⟩