The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task
Rachel Bawden, Alexandra Birch, Radina Dobreva, Arturo Oncevay, Antonio Valerio Miceli Barone, Philip Williams
Abstract
We describe the University of Edinburgh’s submissions to the WMT20 news translation shared task for the low resource language pair English-Tamil and the mid-resource language pair English-Inuktitut. We use the neural machine translation transformer architecture for all submissions and explore a variety of techniques to improve translation quality to compensate for the lack of parallel training data. For the very low-resource English-Tamil, this involves exploring pretraining, using both language model objectives and translation using an unrelated high-resource language pair (German-English), and iterative backtranslation. For English-Inuktitut, we explore the use of multilingual systems, which, despite not being part of the primary submission, would have achieved the best results on the test set.- Anthology ID:
- 2020.wmt-1.5
- 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:
- 92–99
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.5
- DOI:
- Cite (ACL):
- Rachel Bawden, Alexandra Birch, Radina Dobreva, Arturo Oncevay, Antonio Valerio Miceli Barone, and Philip Williams. 2020. The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 92–99, Online. Association for Computational Linguistics.
- Cite (Informal):
- The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task (Bawden et al., WMT 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.wmt-1.5.pdf