Abstract
This paper describes the ADAPT Centre’s submissions to the WMT20 Biomedical Translation Shared Task for English-to-Basque. We present the machine translation (MT) systems that were built to translate scientific abstracts and terms from biomedical terminologies, and using the state-of-the-art neural MT (NMT) model: Transformer. In order to improve our baseline NMT system, we employ a number of methods, e.g. “pseudo” parallel data selection, monolingual data selection for synthetic corpus creation, mining monolingual sentences for adapting our NMT systems to this task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that systematic addition of the aforementioned techniques to the baseline yields an excellent performance in the English-to-Basque translation task.- Anthology ID:
- 2020.wmt-1.91
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 841–848
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.91
- DOI:
- Cite (ACL):
- Prashant Nayak, Rejwanul Haque, and Andy Way. 2020. The ADAPT’s Submissions to the WMT20 Biomedical Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 841–848, Online. Association for Computational Linguistics.
- Cite (Informal):
- The ADAPT’s Submissions to the WMT20 Biomedical Translation Task (Nayak et al., WMT 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2020.wmt-1.91.pdf