Abstract
This paper describes our submission to the Word-Level AutoCompletion shared task of WMT22. We participated in the English–German and German–English categories. We proposed a segment-based interactive machine translation approach whose central core is a machine translation (MT) model which generates a complete translation from the context provided by the task. From there, we obtain the word which corresponds to the autocompletion. With this approach, we aim to show that it is possible to use the MT models in the autocompletion task by simply performing minor changes at the decoding step, obtaining satisfactory results.- Anthology ID:
- 2022.wmt-1.120
- 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:
- 1182–1186
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.120
- DOI:
- Bibkey:
- Cite (ACL):
- Angel Navarro, Miguel Domingo, and Francisco Casacuberta. 2022. PRHLT’s Submission to WLAC 2022. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1182–1186, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- PRHLT’s Submission to WLAC 2022 (Navarro et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.120.pdf
Export citation
@inproceedings{navarro-etal-2022-prhlts,
title = "{PRHLT}{'}s Submission to {WLAC} 2022",
author = "Navarro, Angel and
Domingo, Miguel and
Casacuberta, Francisco",
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-1.120",
pages = "1182--1186",
abstract = "This paper describes our submission to the Word-Level AutoCompletion shared task of WMT22. We participated in the English{--}German and German{--}English categories. We proposed a segment-based interactive machine translation approach whose central core is a machine translation (MT) model which generates a complete translation from the context provided by the task. From there, we obtain the word which corresponds to the autocompletion. With this approach, we aim to show that it is possible to use the MT models in the autocompletion task by simply performing minor changes at the decoding step, obtaining satisfactory results.",
}
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%0 Conference Proceedings %T PRHLT’s Submission to WLAC 2022 %A Navarro, Angel %A Domingo, Miguel %A Casacuberta, Francisco %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 navarro-etal-2022-prhlts %X This paper describes our submission to the Word-Level AutoCompletion shared task of WMT22. We participated in the English–German and German–English categories. We proposed a segment-based interactive machine translation approach whose central core is a machine translation (MT) model which generates a complete translation from the context provided by the task. From there, we obtain the word which corresponds to the autocompletion. With this approach, we aim to show that it is possible to use the MT models in the autocompletion task by simply performing minor changes at the decoding step, obtaining satisfactory results. %U https://aclanthology.org/2022.wmt-1.120 %P 1182-1186
Markdown (Informal)
[PRHLT’s Submission to WLAC 2022](https://aclanthology.org/2022.wmt-1.120) (Navarro et al., WMT 2022)
- PRHLT’s Submission to WLAC 2022 (Navarro et al., WMT 2022)
ACL
- Angel Navarro, Miguel Domingo, and Francisco Casacuberta. 2022. PRHLT’s Submission to WLAC 2022. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1182–1186, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.