Abstract
This review depicts our submission to the WMT20 shared news translation task. WMT is the conference to assess the level of machine translation capabilities of organizations in the word. We participated in one language pair and two language directions, from Russian to English and from English to Russian. We used official training data, 102 million parallel corpora and 10 million monolingual corpora. Our baseline systems are Transformer models trained with the Sockeye sequence modeling toolkit, supplemented by bi-text data filtering schemes, back-translations, reordering and other related processing methods. The BLEU value of our translation result from Russian to English is 35.7, ranking 5th, while from English to Russian is 39.8, ranking 2th.- Anthology ID:
- 2020.wmt-1.35
- 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:
- 320–325
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.35
- DOI:
- Cite (ACL):
- Ariel Xv. 2020. Russian-English Bidirectional Machine Translation System. In Proceedings of the Fifth Conference on Machine Translation, pages 320–325, Online. Association for Computational Linguistics.
- Cite (Informal):
- Russian-English Bidirectional Machine Translation System (Xv, WMT 2020)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2020.wmt-1.35.pdf