WeChat Neural Machine Translation Systems for WMT20
Fandong Meng, Jianhao Yan, Yijin Liu, Yuan Gao, Xianfeng Zeng, Qinsong Zeng, Peng Li, Ming Chen, Jie Zhou, Sifan Liu, Hao Zhou
Abstract
We participate in the WMT 2020 shared newstranslation task on Chinese→English. Our system is based on the Transformer (Vaswaniet al., 2017a) with effective variants and the DTMT (Meng and Zhang, 2019) architecture. In our experiments, we employ data selection, several synthetic data generation approaches (i.e., back-translation, knowledge distillation, and iterative in-domain knowledge transfer), advanced finetuning approaches and self-bleu based model ensemble. Our constrained Chinese→English system achieves 36.9 case-sensitive BLEU score, which is thehighest among all submissions.- Anthology ID:
- 2020.wmt-1.24
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 239–247
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.24
- DOI:
- Bibkey:
- Cite (ACL):
- Fandong Meng, Jianhao Yan, Yijin Liu, Yuan Gao, Xianfeng Zeng, Qinsong Zeng, Peng Li, Ming Chen, Jie Zhou, Sifan Liu, and Hao Zhou. 2020. WeChat Neural Machine Translation Systems for WMT20. In Proceedings of the Fifth Conference on Machine Translation, pages 239–247, Online. Association for Computational Linguistics.
- Cite (Informal):
- WeChat Neural Machine Translation Systems for WMT20 (Meng et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.24.pdf
- Video:
- https://slideslive.com/38939596
Export citation
@inproceedings{meng-etal-2020-wechat,
title = "{W}e{C}hat Neural Machine Translation Systems for {WMT}20",
author = "Meng, Fandong and
Yan, Jianhao and
Liu, Yijin and
Gao, Yuan and
Zeng, Xianfeng and
Zeng, Qinsong and
Li, Peng and
Chen, Ming and
Zhou, Jie and
Liu, Sifan and
Zhou, Hao",
editor = {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
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.24",
pages = "239--247",
abstract = "We participate in the WMT 2020 shared newstranslation task on Chinese→English. Our system is based on the Transformer (Vaswaniet al., 2017a) with effective variants and the DTMT (Meng and Zhang, 2019) architecture. In our experiments, we employ data selection, several synthetic data generation approaches (i.e., back-translation, knowledge distillation, and iterative in-domain knowledge transfer), advanced finetuning approaches and self-bleu based model ensemble. Our constrained Chinese→English system achieves 36.9 case-sensitive BLEU score, which is thehighest among all submissions.",
}
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%0 Conference Proceedings %T WeChat Neural Machine Translation Systems for WMT20 %A Meng, Fandong %A Yan, Jianhao %A Liu, Yijin %A Gao, Yuan %A Zeng, Xianfeng %A Zeng, Qinsong %A Li, Peng %A Chen, Ming %A Zhou, Jie %A Liu, Sifan %A Zhou, Hao %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 Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F meng-etal-2020-wechat %X We participate in the WMT 2020 shared newstranslation task on Chinese→English. Our system is based on the Transformer (Vaswaniet al., 2017a) with effective variants and the DTMT (Meng and Zhang, 2019) architecture. In our experiments, we employ data selection, several synthetic data generation approaches (i.e., back-translation, knowledge distillation, and iterative in-domain knowledge transfer), advanced finetuning approaches and self-bleu based model ensemble. Our constrained Chinese→English system achieves 36.9 case-sensitive BLEU score, which is thehighest among all submissions. %U https://aclanthology.org/2020.wmt-1.24 %P 239-247
Markdown (Informal)
[WeChat Neural Machine Translation Systems for WMT20](https://aclanthology.org/2020.wmt-1.24) (Meng et al., WMT 2020)
- WeChat Neural Machine Translation Systems for WMT20 (Meng et al., WMT 2020)
ACL
- Fandong Meng, Jianhao Yan, Yijin Liu, Yuan Gao, Xianfeng Zeng, Qinsong Zeng, Peng Li, Ming Chen, Jie Zhou, Sifan Liu, and Hao Zhou. 2020. WeChat Neural Machine Translation Systems for WMT20. In Proceedings of the Fifth Conference on Machine Translation, pages 239–247, Online. Association for Computational Linguistics.