Findings of the WMT 2020 Shared Task on Machine Translation Robustness

Lucia Specia, Zhenhao Li, Juan Pino, Vishrav Chaudhary, Francisco Guzmán, Graham Neubig, Nadir Durrani, Yonatan Belinkov, Philipp Koehn, Hassan Sajjad, Paul Michel, Xian Li


Abstract
We report the findings of the second edition of the shared task on improving robustness in Machine Translation (MT). The task aims to test current machine translation systems in their ability to handle challenges facing MT models to be deployed in the real world, including domain diversity and non-standard texts common in user generated content, especially in social media. We cover two language pairs – English-German and English-Japanese and provide test sets in zero-shot and few-shot variants. Participating systems are evaluated both automatically and manually, with an additional human evaluation for ”catastrophic errors”. We received 59 submissions by 11 participating teams from a variety of types of institutions.
Anthology ID:
2020.wmt-1.4
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
76–91
Language:
URL:
https://aclanthology.org/2020.wmt-1.4
DOI:
Bibkey:
Cite (ACL):
Lucia Specia, Zhenhao Li, Juan Pino, Vishrav Chaudhary, Francisco Guzmán, Graham Neubig, Nadir Durrani, Yonatan Belinkov, Philipp Koehn, Hassan Sajjad, Paul Michel, and Xian Li. 2020. Findings of the WMT 2020 Shared Task on Machine Translation Robustness. In Proceedings of the Fifth Conference on Machine Translation, pages 76–91, Online. Association for Computational Linguistics.
Cite (Informal):
Findings of the WMT 2020 Shared Task on Machine Translation Robustness (Specia et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.4.pdf
Video:
 https://slideslive.com/38939676
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