@proceedings{Berard_A-2020_9763,
title = {Naver Labs Europe's Participation in the Robustness, Chat, and Biomedical Tasks at WMT 2020},
author = {Berard, A. and Calapodescu, I. and Nikoulina, V. and Philip, J.},
month = {nov},
year = {2020},
abstract = {This paper describes Naver Labs Europe's participation in the Robustness, Chat, and Biomedical Translation tasks at WMT 2020. We propose a bidirectional German-English model that is multi-domain, robust to noise, and which can translate entire documents (or bilingual dialogues) at once. We use the same ensemble of such models as our primary submission to all three tasks and achieve competitive results. We also experiment with language model pre-training techniques and evaluate their impact on robustness to noise and out-of-domain translation. For German, Spanish, Italian, and French to English translation in the Biomedical Task, we also submit our recently released multilingual Covid19NMT model.},
pages = {462-472},
journal = {Proceedings of the Fifth Conference on Machine Translation},
publisher = {Association for Computational Linguistics},
url = {https://publichealthscotland.scot/id/9763},
}
