Findings of the WMT 2021 Shared Task on Quality Estimation

Lucia Specia, Frédéric Blain, Marina Fomicheva, Chrysoula Zerva, Zhenhao Li, Vishrav Chaudhary, André F. T. Martins


Abstract
We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels. This edition focused on two main novel additions: (i) prediction for unseen languages, i.e. zero-shot settings, and (ii) prediction of sentences with catastrophic errors. In addition, new data was released for a number of languages, especially post-edited data. Participating teams from 19 institutions submitted altogether 1263 systems to different task variants and language pairs.
Anthology ID:
2021.wmt-1.71
Volume:
Proceedings of the Sixth Conference on Machine Translation
Month:
November
Year:
2021
Address:
Online
Venues:
EMNLP | WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
684–725
Language:
URL:
https://aclanthology.org/2021.wmt-1.71
DOI:
Bibkey:
Cite (ACL):
Lucia Specia, Frédéric Blain, Marina Fomicheva, Chrysoula Zerva, Zhenhao Li, Vishrav Chaudhary, and André F. T. Martins. 2021. Findings of the WMT 2021 Shared Task on Quality Estimation. In Proceedings of the Sixth Conference on Machine Translation, pages 684–725, Online. Association for Computational Linguistics.
Cite (Informal):
Findings of the WMT 2021 Shared Task on Quality Estimation (Specia et al., WMT 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.wmt-1.71.pdf
Data
MLQE-PE