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
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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
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- 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)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.69.pdf
- Video:
- https://aclanthology.org/2021.wmt-1.69.mp4
Export citation
@inproceedings{alam-etal-2021-findings,
title = "Findings of the {WMT} Shared Task on Machine Translation Using Terminologies",
author = "Alam, Md Mahfuz Ibn and
Kvapil{\'i}kov{\'a}, Ivana and
Anastasopoulos, Antonios and
Besacier, Laurent and
Dinu, Georgiana and
Federico, Marcello and
Gall{\'e}, Matthias and
Jung, Kweonwoo and
Koehn, Philipp and
Nikoulina, Vassilina",
editor = "Barrault, Loic and
Bojar, Ondrej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-jussa, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Kocmi, Tom and
Martins, Andre and
Morishita, Makoto and
Monz, Christof",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.69/",
pages = "652--663",
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."
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%0 Conference Proceedings %T Findings of the WMT Shared Task on Machine Translation Using Terminologies %A Alam, Md Mahfuz Ibn %A Kvapilíková, Ivana %A Anastasopoulos, Antonios %A Besacier, Laurent %A Dinu, Georgiana %A Federico, Marcello %A Gallé, Matthias %A Jung, Kweonwoo %A Koehn, Philipp %A Nikoulina, Vassilina %Y Barrault, Loic %Y Bojar, Ondrej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussa, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Kocmi, Tom %Y Martins, Andre %Y Morishita, Makoto %Y Monz, Christof %S Proceedings of the Sixth Conference on Machine Translation %D 2021 %8 November %I Association for Computational Linguistics %C Online %F alam-etal-2021-findings %X 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. %U https://aclanthology.org/2021.wmt-1.69/ %P 652-663
Markdown (Informal)
[Findings of the WMT Shared Task on Machine Translation Using Terminologies](https://aclanthology.org/2021.wmt-1.69/) (Alam et al., WMT 2021)
- Findings of the WMT Shared Task on Machine Translation Using Terminologies (Alam et al., WMT 2021)
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.