Abstract
This paper describes the PROMT submissions for the WMT21 Terminology Translation Task. We participate in two directions: English to French and English to Russian. Our final submissions are MarianNMT-based neural systems. We present two technologies for terminology translation: a modification of the Dinu et al. (2019) soft-constrained approach and our own approach called PROMT Smart Neural Dictionary (SmartND). We achieve good results in both directions.- Anthology ID:
- 2021.wmt-1.83
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 835–841
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.83
- DOI:
- Cite (ACL):
- Alexander Molchanov, Vladislav Kovalenko, and Fedor Bykov. 2021. PROMT Systems for WMT21 Terminology Translation Task. In Proceedings of the Sixth Conference on Machine Translation, pages 835–841, Online. Association for Computational Linguistics.
- Cite (Informal):
- PROMT Systems for WMT21 Terminology Translation Task (Molchanov et al., WMT 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.wmt-1.83.pdf