Abstract
We present the findings of the WMT2021 Shared Tasks in Unsupervised MT and Very Low Resource Supervised MT. Within the task, the community studied very low resource translation between German and Upper Sorbian, unsupervised translation between German and Lower Sorbian and low resource translation between Russian and Chuvash, all minority languages with active language communities working on preserving the languages, who are partners in the evaluation. Thanks to this, we were able to obtain most digital data available for these languages and offer them to the task participants. In total, six teams participated in the shared task. The paper discusses the background, presents the tasks and results, and discusses best practices for the future.- Anthology ID:
- 2021.wmt-1.72
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 726–732
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.72
- DOI:
- Cite (ACL):
- Jindřich Libovický and Alexander Fraser. 2021. Findings of the WMT 2021 Shared Tasks in Unsupervised MT and Very Low Resource Supervised MT. In Proceedings of the Sixth Conference on Machine Translation, pages 726–732, Online. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the WMT 2021 Shared Tasks in Unsupervised MT and Very Low Resource Supervised MT (Libovický & Fraser, WMT 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.wmt-1.72.pdf