Abstract
We present our submissions to the WMT21 shared task in Unsupervised and Very Low Resource machine translation between German and Upper Sorbian, German and Lower Sorbian, and Russian and Chuvash. Our low-resource systems (German↔Upper Sorbian, Russian↔Chuvash) are pre-trained on high-resource pairs of related languages. We fine-tune those systems using the available authentic parallel data and improve by iterated back-translation. The unsupervised German↔Lower Sorbian system is initialized by the best Upper Sorbian system and improved by iterated back-translation using monolingual data only.- Anthology ID:
- 2021.wmt-1.105
- 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:
- 989–994
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.105
- DOI:
- Cite (ACL):
- Jindřich Libovický and Alexander Fraser. 2021. The LMU Munich Systems for the WMT21 Unsupervised and Very Low-Resource Translation Task. In Proceedings of the Sixth Conference on Machine Translation, pages 989–994, Online. Association for Computational Linguistics.
- Cite (Informal):
- The LMU Munich Systems for the WMT21 Unsupervised and Very Low-Resource Translation Task (Libovický & Fraser, WMT 2021)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2021.wmt-1.105.pdf