Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task
Melissa Ailem, Jingshu Liu, Jean-gabriel Barthelemy, Raheel Qader
Correct Metadata for
Abstract
This paper presents Lingua Custodia’s submission to the WMT22 shared task on Word Level Auto-completion (WLAC). We consider two directions, namely German-English and English-German.The WLAC task in Neural Machine Translation (NMT) consists in predicting a target word given few human typed characters, the source sentence to translate, as well as some translation context. Inspired by recent work in terminology control, we propose to treat the human typed sequence as a constraint to predict the right word starting by the latter. To do so, the source side of the training data is augmented with both the constraints and the translation context. In addition, following new advances in WLAC, we use a joint optimization strategy taking into account several types of translation context. The automatic as well as human accuracy obtained with the submitted systems show the effectiveness of the proposed method.- Anthology ID:
- 2022.wmt-1.118
- Volume:
- Proceedings of the Seventh Conference on Machine Translation (WMT)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1170–1175
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.118/
- DOI:
- Bibkey:
- Cite (ACL):
- Melissa Ailem, Jingshu Liu, Jean-gabriel Barthelemy, and Raheel Qader. 2022. Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1170–1175, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task (Ailem et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.118.pdf
Export citation
@inproceedings{ailem-etal-2022-lingua,
title = "Lingua Custodia`s Participation at the {WMT} 2022 Word-Level Auto-completion Shared Task",
author = "Ailem, Melissa and
Liu, Jingshu and
Barthelemy, Jean-gabriel and
Qader, Raheel",
editor = {Koehn, Philipp and
Barrault, Lo{\"i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, 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
Jimeno Yepes, Antonio and
Kocmi, Tom and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Popel, Martin and
Turchi, Marco and
Zampieri, Marcos},
booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wmt-1.118/",
pages = "1170--1175",
abstract = "This paper presents Lingua Custodia`s submission to the WMT22 shared task on Word Level Auto-completion (WLAC). We consider two directions, namely German-English and English-German.The WLAC task in Neural Machine Translation (NMT) consists in predicting a target word given few human typed characters, the source sentence to translate, as well as some translation context. Inspired by recent work in terminology control, we propose to treat the human typed sequence as a constraint to predict the right word starting by the latter. To do so, the source side of the training data is augmented with both the constraints and the translation context. In addition, following new advances in WLAC, we use a joint optimization strategy taking into account several types of translation context. The automatic as well as human accuracy obtained with the submitted systems show the effectiveness of the proposed method."
}
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%0 Conference Proceedings %T Lingua Custodia‘s Participation at the WMT 2022 Word-Level Auto-completion Shared Task %A Ailem, Melissa %A Liu, Jingshu %A Barthelemy, Jean-gabriel %A Qader, Raheel %Y Koehn, Philipp %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, 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 Jimeno Yepes, Antonio %Y Kocmi, Tom %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Popel, Martin %Y Turchi, Marco %Y Zampieri, Marcos %S Proceedings of the Seventh Conference on Machine Translation (WMT) %D 2022 %8 December %I Association for Computational Linguistics %C Abu Dhabi, United Arab Emirates (Hybrid) %F ailem-etal-2022-lingua %X This paper presents Lingua Custodia‘s submission to the WMT22 shared task on Word Level Auto-completion (WLAC). We consider two directions, namely German-English and English-German.The WLAC task in Neural Machine Translation (NMT) consists in predicting a target word given few human typed characters, the source sentence to translate, as well as some translation context. Inspired by recent work in terminology control, we propose to treat the human typed sequence as a constraint to predict the right word starting by the latter. To do so, the source side of the training data is augmented with both the constraints and the translation context. In addition, following new advances in WLAC, we use a joint optimization strategy taking into account several types of translation context. The automatic as well as human accuracy obtained with the submitted systems show the effectiveness of the proposed method. %U https://aclanthology.org/2022.wmt-1.118/ %P 1170-1175
Markdown (Informal)
[Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task](https://aclanthology.org/2022.wmt-1.118/) (Ailem et al., WMT 2022)
- Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task (Ailem et al., WMT 2022)
ACL
- Melissa Ailem, Jingshu Liu, Jean-gabriel Barthelemy, and Raheel Qader. 2022. Lingua Custodia’s Participation at the WMT 2022 Word-Level Auto-completion Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1170–1175, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.