Findings of the WMT Shared Task on Machine Translation Using Terminologies

Md Mahfuz Ibn Alam, Ivana Kvapilíková, Antonios Anastasopoulos, Laurent Besacier, Georgiana Dinu, Marcello Federico, Matthias Gallé, Kweonwoo Jung, Philipp Koehn, Vassilina Nikoulina


Abstract
Language domains that require very careful use of terminology are abundant and reflect a significant part of the translation industry. In this work we introduce a benchmark for evaluating the quality and consistency of terminology translation, focusing on the medical (and COVID-19 specifically) domain for five language pairs: English to French, Chinese, Russian, and Korean, as well as Czech to German. We report the descriptions and results of the participating systems, commenting on the need for further research efforts towards both more adequate handling of terminologies as well as towards a proper formulation and evaluation of the task.
Anthology ID:
2021.wmt-1.69
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:
652–663
Language:
URL:
https://aclanthology.org/2021.wmt-1.69
DOI:
Bibkey:
Cite (ACL):
Md Mahfuz Ibn Alam, Ivana Kvapilíková, Antonios Anastasopoulos, Laurent Besacier, Georgiana Dinu, Marcello Federico, Matthias Gallé, Kweonwoo Jung, Philipp Koehn, and Vassilina Nikoulina. 2021. Findings of the WMT Shared Task on Machine Translation Using Terminologies. In Proceedings of the Sixth Conference on Machine Translation, pages 652–663, Online. Association for Computational Linguistics.
Cite (Informal):
Findings of the WMT Shared Task on Machine Translation Using Terminologies (Alam et al., WMT 2021)
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https://preview.aclanthology.org/update-css-js/2021.wmt-1.69.pdf