HW-TSC’s Participation in the WMT 2021 News Translation Shared Task
Daimeng Wei, Zongyao Li, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, Ying Qin
Correct Metadata for
Abstract
This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT 2021 News Translation Shared Task. We participate in 7 language pairs, including Zh/En, De/En, Ja/En, Ha/En, Is/En, Hi/Bn, and Xh/Zu in both directions under the constrained condition. We use Transformer architecture and obtain the best performance via multiple variants with larger parameter sizes. We perform detailed pre-processing and filtering on the provided large-scale bilingual and monolingual datasets. Several commonly used strategies are used to train our models, such as Back Translation, Forward Translation, Multilingual Translation, Ensemble Knowledge Distillation, etc. Our submission obtains competitive results in the final evaluation.- Anthology ID:
- 2021.wmt-1.21
- 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:
- 225–231
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.21/
- DOI:
- Bibkey:
- Cite (ACL):
- Daimeng Wei, Zongyao Li, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, and Ying Qin. 2021. HW-TSC’s Participation in the WMT 2021 News Translation Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 225–231, Online. Association for Computational Linguistics.
- Cite (Informal):
- HW-TSC’s Participation in the WMT 2021 News Translation Shared Task (Wei et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.21.pdf
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@inproceedings{wei-etal-2021-hw,
title = "{HW}-{TSC}{'}s Participation in the {WMT} 2021 News Translation Shared Task",
author = "Wei, Daimeng and
Li, Zongyao and
Wu, Zhanglin and
Yu, Zhengzhe and
Chen, Xiaoyu and
Shang, Hengchao and
Guo, Jiaxin and
Wang, Minghan and
Lei, Lizhi and
Zhang, Min and
Yang, Hao and
Qin, Ying",
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-1.21/",
pages = "225--231",
abstract = "This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT 2021 News Translation Shared Task. We participate in 7 language pairs, including Zh/En, De/En, Ja/En, Ha/En, Is/En, Hi/Bn, and Xh/Zu in both directions under the constrained condition. We use Transformer architecture and obtain the best performance via multiple variants with larger parameter sizes. We perform detailed pre-processing and filtering on the provided large-scale bilingual and monolingual datasets. Several commonly used strategies are used to train our models, such as Back Translation, Forward Translation, Multilingual Translation, Ensemble Knowledge Distillation, etc. Our submission obtains competitive results in the final evaluation."
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%0 Conference Proceedings %T HW-TSC’s Participation in the WMT 2021 News Translation Shared Task %A Wei, Daimeng %A Li, Zongyao %A Wu, Zhanglin %A Yu, Zhengzhe %A Chen, Xiaoyu %A Shang, Hengchao %A Guo, Jiaxin %A Wang, Minghan %A Lei, Lizhi %A Zhang, Min %A Yang, Hao %A Qin, Ying %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 wei-etal-2021-hw %X This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT 2021 News Translation Shared Task. We participate in 7 language pairs, including Zh/En, De/En, Ja/En, Ha/En, Is/En, Hi/Bn, and Xh/Zu in both directions under the constrained condition. We use Transformer architecture and obtain the best performance via multiple variants with larger parameter sizes. We perform detailed pre-processing and filtering on the provided large-scale bilingual and monolingual datasets. Several commonly used strategies are used to train our models, such as Back Translation, Forward Translation, Multilingual Translation, Ensemble Knowledge Distillation, etc. Our submission obtains competitive results in the final evaluation. %U https://aclanthology.org/2021.wmt-1.21/ %P 225-231
Markdown (Informal)
[HW-TSC’s Participation in the WMT 2021 News Translation Shared Task](https://aclanthology.org/2021.wmt-1.21/) (Wei et al., WMT 2021)
- HW-TSC’s Participation in the WMT 2021 News Translation Shared Task (Wei et al., WMT 2021)
ACL
- Daimeng Wei, Zongyao Li, Zhanglin Wu, Zhengzhe Yu, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Minghan Wang, Lizhi Lei, Min Zhang, Hao Yang, and Ying Qin. 2021. HW-TSC’s Participation in the WMT 2021 News Translation Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 225–231, Online. Association for Computational Linguistics.