@inproceedings{specia-etal-2020-findings,
title = "Findings of the {WMT} 2020 Shared Task on Machine Translation Robustness",
author = "Specia, Lucia and
Li, Zhenhao and
Pino, Juan and
Chaudhary, Vishrav and
Guzm{\'a}n, Francisco and
Neubig, Graham and
Durrani, Nadir and
Belinkov, Yonatan and
Koehn, Philipp and
Sajjad, Hassan and
Michel, Paul and
Li, Xian",
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.4",
pages = "76--91",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Findings of the WMT 2020 Shared Task on Machine Translation Robustness
%A Specia, Lucia
%A Li, Zhenhao
%A Pino, Juan
%A Chaudhary, Vishrav
%A Guzmán, Francisco
%A Neubig, Graham
%A Durrani, Nadir
%A Belinkov, Yonatan
%A Koehn, Philipp
%A Sajjad, Hassan
%A Michel, Paul
%A Li, Xian
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F specia-etal-2020-findings
%X 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.
%U https://aclanthology.org/2020.wmt-1.4
%P 76-91
Markdown (Informal)
[Findings of the WMT 2020 Shared Task on Machine Translation Robustness](https://aclanthology.org/2020.wmt-1.4) (Specia et al., WMT 2020)
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.