Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task
Jian Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Li Dong, Shaohan Huang, Alexandre Muzio, Saksham Singhal, Hany Hassan, Xia Song, Furu Wei
Abstract
This report describes Microsoft’s machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tracks including Large Track and two Small Tracks where the former one is unconstrained and the latter two are fully constrained. Our model submissions to the shared task were initialized with DeltaLM, a generic pre-trained multilingual encoder-decoder model, and fine-tuned correspondingly with the vast collected parallel data and allowed data sources according to track settings, together with applying progressive learning and iterative back-translation approaches to further improve the performance. Our final submissions ranked first on three tracks in terms of the automatic evaluation metric.- Anthology ID:
- 2021.wmt-1.54
- 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:
- 446–455
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.54
- DOI:
- Bibkey:
- Cite (ACL):
- Jian Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Li Dong, Shaohan Huang, Alexandre Muzio, Saksham Singhal, Hany Hassan, Xia Song, and Furu Wei. 2021. Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 446–455, Online. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task (Yang et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.54.pdf
- Data
- FLoRes-101
Export citation
@inproceedings{yang-etal-2021-multilingual-machine,
title = "Multilingual Machine Translation Systems from {M}icrosoft for {WMT}21 Shared Task",
author = "Yang, Jian and
Ma, Shuming and
Huang, Haoyang and
Zhang, Dongdong and
Dong, Li and
Huang, Shaohan and
Muzio, Alexandre and
Singhal, Saksham and
Hassan, Hany and
Song, Xia and
Wei, Furu",
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-1.54",
pages = "446--455",
abstract = "This report describes Microsoft{'}s machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tracks including Large Track and two Small Tracks where the former one is unconstrained and the latter two are fully constrained. Our model submissions to the shared task were initialized with DeltaLM, a generic pre-trained multilingual encoder-decoder model, and fine-tuned correspondingly with the vast collected parallel data and allowed data sources according to track settings, together with applying progressive learning and iterative back-translation approaches to further improve the performance. Our final submissions ranked first on three tracks in terms of the automatic evaluation metric.",
}
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%0 Conference Proceedings %T Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task %A Yang, Jian %A Ma, Shuming %A Huang, Haoyang %A Zhang, Dongdong %A Dong, Li %A Huang, Shaohan %A Muzio, Alexandre %A Singhal, Saksham %A Hassan, Hany %A Song, Xia %A Wei, Furu %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 yang-etal-2021-multilingual-machine %X This report describes Microsoft’s machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tracks including Large Track and two Small Tracks where the former one is unconstrained and the latter two are fully constrained. Our model submissions to the shared task were initialized with DeltaLM, a generic pre-trained multilingual encoder-decoder model, and fine-tuned correspondingly with the vast collected parallel data and allowed data sources according to track settings, together with applying progressive learning and iterative back-translation approaches to further improve the performance. Our final submissions ranked first on three tracks in terms of the automatic evaluation metric. %U https://aclanthology.org/2021.wmt-1.54 %P 446-455
Markdown (Informal)
[Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task](https://aclanthology.org/2021.wmt-1.54) (Yang et al., WMT 2021)
- Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task (Yang et al., WMT 2021)
ACL
- Jian Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Li Dong, Shaohan Huang, Alexandre Muzio, Saksham Singhal, Hany Hassan, Xia Song, and Furu Wei. 2021. Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 446–455, Online. Association for Computational Linguistics.