Abstract
This paper describes Tilde’s submission to the WMT2020 shared task on news translation for both directions of the English-Polish language pair in both the constrained and the unconstrained tracks. We follow our submissions form the previous years and build our baseline systems to be morphologically motivated sub-word unit-based Transformer base models that we train using the Marian machine translation toolkit. Additionally, we experiment with different parallel and monolingual data selection schemes, as well as sampled back-translation. Our final models are ensembles of Transformer base and Transformer big models which feature right-to-left re-ranking.- Anthology ID:
- 2020.wmt-1.15
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 175–180
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.15
- DOI:
- Cite (ACL):
- Rihards Krišlauks and Mārcis Pinnis. 2020. Tilde at WMT 2020: News Task Systems. In Proceedings of the Fifth Conference on Machine Translation, pages 175–180, Online. Association for Computational Linguistics.
- Cite (Informal):
- Tilde at WMT 2020: News Task Systems (Krišlauks & Pinnis, WMT 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.wmt-1.15.pdf
- Data
- ParaCrawl