Huawei’s Submissions to the WMT20 Biomedical Translation Task
Wei Peng, Jianfeng Liu, Minghan Wang, Liangyou Li, Xupeng Meng, Hao Yang, Qun Liu
Abstract
This paper describes Huawei’s submissions to the WMT20 biomedical translation shared task. Apart from experimenting with finetuning on domain-specific bitexts, we explore effects of in-domain dictionaries on enhancing cross-domain neural machine translation performance. We utilize a transfer learning strategy through pre-trained machine translation models and extensive scope of engineering endeavors. Four of our ten submissions achieve state-of-the-art performance according to the official automatic evaluation results, namely translation directions on English<->French, English->German and English->Italian.- Anthology ID:
- 2020.wmt-1.93
- 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:
- 857–861
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.93
- DOI:
- Bibkey:
- Cite (ACL):
- Wei Peng, Jianfeng Liu, Minghan Wang, Liangyou Li, Xupeng Meng, Hao Yang, and Qun Liu. 2020. Huawei’s Submissions to the WMT20 Biomedical Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 857–861, Online. Association for Computational Linguistics.
- Cite (Informal):
- Huawei’s Submissions to the WMT20 Biomedical Translation Task (Peng et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.93.pdf
- Video:
- https://slideslive.com/38939576
Export citation
@inproceedings{peng-etal-2020-huaweis,
title = "Huawei{'}s Submissions to the {WMT}20 Biomedical Translation Task",
author = "Peng, Wei and
Liu, Jianfeng and
Wang, Minghan and
Li, Liangyou and
Meng, Xupeng and
Yang, Hao and
Liu, Qun",
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-1.93",
pages = "857--861",
abstract = "This paper describes Huawei{'}s submissions to the WMT20 biomedical translation shared task. Apart from experimenting with finetuning on domain-specific bitexts, we explore effects of in-domain dictionaries on enhancing cross-domain neural machine translation performance. We utilize a transfer learning strategy through pre-trained machine translation models and extensive scope of engineering endeavors. Four of our ten submissions achieve state-of-the-art performance according to the official automatic evaluation results, namely translation directions on English{\textless}-{\textgreater}French, English-{\textgreater}German and English-{\textgreater}Italian.",
}
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%0 Conference Proceedings %T Huawei’s Submissions to the WMT20 Biomedical Translation Task %A Peng, Wei %A Liu, Jianfeng %A Wang, Minghan %A Li, Liangyou %A Meng, Xupeng %A Yang, Hao %A Liu, Qun %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 peng-etal-2020-huaweis %X This paper describes Huawei’s submissions to the WMT20 biomedical translation shared task. Apart from experimenting with finetuning on domain-specific bitexts, we explore effects of in-domain dictionaries on enhancing cross-domain neural machine translation performance. We utilize a transfer learning strategy through pre-trained machine translation models and extensive scope of engineering endeavors. Four of our ten submissions achieve state-of-the-art performance according to the official automatic evaluation results, namely translation directions on English\textless-\textgreaterFrench, English-\textgreaterGerman and English-\textgreaterItalian. %U https://aclanthology.org/2020.wmt-1.93 %P 857-861
Markdown (Informal)
[Huawei’s Submissions to the WMT20 Biomedical Translation Task](https://aclanthology.org/2020.wmt-1.93) (Peng et al., WMT 2020)
- Huawei’s Submissions to the WMT20 Biomedical Translation Task (Peng et al., WMT 2020)
ACL
- Wei Peng, Jianfeng Liu, Minghan Wang, Liangyou Li, Xupeng Meng, Hao Yang, and Qun Liu. 2020. Huawei’s Submissions to the WMT20 Biomedical Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 857–861, Online. Association for Computational Linguistics.