BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task
Hui Huang, Hui Di, Chunyou Li, Hanming Wu, Kazushige Ouchi, Yufeng Chen, Jian Liu, Jinan Xu
Abstract
This paper presents the BJTU-Toshiba joint submission for WMT 2022 quality estimation shared task. We only participate in Task 1 (quality prediction) of the shared task, focusing on the sentence-level MQM prediction. The techniques we experimented with include the integration of monolingual language models and the pre-finetuning of pre-trained representations. We tried two styles of pre-finetuning, namely Translation Language Modeling and Replaced Token Detection. We demonstrate the competitiveness of our system compared to the widely adopted XLM-RoBERTa baseline. Our system is also the top-ranking system on the Sentence-level MQM Prediction for the English-German language pairs.- Anthology ID:
- 2022.wmt-1.58
- 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:
- 621–626
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.58
- DOI:
- Bibkey:
- Cite (ACL):
- Hui Huang, Hui Di, Chunyou Li, Hanming Wu, Kazushige Ouchi, Yufeng Chen, Jian Liu, and Jinan Xu. 2022. BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 621–626, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task (Huang et al., WMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.58.pdf
Export citation
@inproceedings{huang-etal-2022-bjtu,
title = "{BJTU}-Toshiba{'}s Submission to {WMT}22 Quality Estimation Shared Task",
author = "Huang, Hui and
Di, Hui and
Li, Chunyou and
Wu, Hanming and
Ouchi, Kazushige and
Chen, Yufeng and
Liu, Jian and
Xu, Jinan",
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-1.58",
pages = "621--626",
abstract = "This paper presents the BJTU-Toshiba joint submission for WMT 2022 quality estimation shared task. We only participate in Task 1 (quality prediction) of the shared task, focusing on the sentence-level MQM prediction. The techniques we experimented with include the integration of monolingual language models and the pre-finetuning of pre-trained representations. We tried two styles of pre-finetuning, namely Translation Language Modeling and Replaced Token Detection. We demonstrate the competitiveness of our system compared to the widely adopted XLM-RoBERTa baseline. Our system is also the top-ranking system on the Sentence-level MQM Prediction for the English-German language pairs.",
}
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%0 Conference Proceedings %T BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task %A Huang, Hui %A Di, Hui %A Li, Chunyou %A Wu, Hanming %A Ouchi, Kazushige %A Chen, Yufeng %A Liu, Jian %A Xu, Jinan %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 huang-etal-2022-bjtu %X This paper presents the BJTU-Toshiba joint submission for WMT 2022 quality estimation shared task. We only participate in Task 1 (quality prediction) of the shared task, focusing on the sentence-level MQM prediction. The techniques we experimented with include the integration of monolingual language models and the pre-finetuning of pre-trained representations. We tried two styles of pre-finetuning, namely Translation Language Modeling and Replaced Token Detection. We demonstrate the competitiveness of our system compared to the widely adopted XLM-RoBERTa baseline. Our system is also the top-ranking system on the Sentence-level MQM Prediction for the English-German language pairs. %U https://aclanthology.org/2022.wmt-1.58 %P 621-626
Markdown (Informal)
[BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.58) (Huang et al., WMT 2022)
- BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task (Huang et al., WMT 2022)
ACL
- Hui Huang, Hui Di, Chunyou Li, Hanming Wu, Kazushige Ouchi, Yufeng Chen, Jian Liu, and Jinan Xu. 2022. BJTU-Toshiba’s Submission to WMT22 Quality Estimation Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 621–626, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.