Abstract
This paper describes our system (Team ID: nictrb) for participating in the WAT’21 restricted machine translation task. In our submitted system, we designed a new training approach for restricted machine translation. By sampling from the translation target, we can solve the problem that ordinary training data does not have a restricted vocabulary. With the further help of constrained decoding in the inference phase, we achieved better results than the baseline, confirming the effectiveness of our solution. In addition, we also tried the vanilla and sparse Transformer as the backbone network of the model, as well as model ensembling, which further improved the final translation performance.- Anthology ID:
- 2021.wat-1.4
- Volume:
- Proceedings of the 8th Workshop on Asian Translation (WAT2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Toshiaki Nakazawa, Hideki Nakayama, Isao Goto, Hideya Mino, Chenchen Ding, Raj Dabre, Anoop Kunchukuttan, Shohei Higashiyama, Hiroshi Manabe, Win Pa Pa, Shantipriya Parida, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Katsuhito Sudoh, Sadao Kurohashi, Pushpak Bhattacharyya
- Venue:
- WAT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 62–67
- Language:
- URL:
- https://aclanthology.org/2021.wat-1.4
- DOI:
- 10.18653/v1/2021.wat-1.4
- Bibkey:
- Cite (ACL):
- Zuchao Li, Masao Utiyama, Eiichiro Sumita, and Hai Zhao. 2021. NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task. In Proceedings of the 8th Workshop on Asian Translation (WAT2021), pages 62–67, Online. Association for Computational Linguistics.
- Cite (Informal):
- NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task (Li et al., WAT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wat-1.4.pdf
Export citation
@inproceedings{li-etal-2021-nicts,
title = "{NICT}{'}s Neural Machine Translation Systems for the {WAT}21 Restricted Translation Task",
author = "Li, Zuchao and
Utiyama, Masao and
Sumita, Eiichiro and
Zhao, Hai",
editor = "Nakazawa, Toshiaki and
Nakayama, Hideki and
Goto, Isao and
Mino, Hideya and
Ding, Chenchen and
Dabre, Raj and
Kunchukuttan, Anoop and
Higashiyama, Shohei and
Manabe, Hiroshi and
Pa, Win Pa and
Parida, Shantipriya and
Bojar, Ond{\v{r}}ej and
Chu, Chenhui and
Eriguchi, Akiko and
Abe, Kaori and
Oda, Yusuke and
Sudoh, Katsuhito and
Kurohashi, Sadao and
Bhattacharyya, Pushpak",
booktitle = "Proceedings of the 8th Workshop on Asian Translation (WAT2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wat-1.4",
doi = "10.18653/v1/2021.wat-1.4",
pages = "62--67",
abstract = "This paper describes our system (Team ID: nictrb) for participating in the WAT{'}21 restricted machine translation task. In our submitted system, we designed a new training approach for restricted machine translation. By sampling from the translation target, we can solve the problem that ordinary training data does not have a restricted vocabulary. With the further help of constrained decoding in the inference phase, we achieved better results than the baseline, confirming the effectiveness of our solution. In addition, we also tried the vanilla and sparse Transformer as the backbone network of the model, as well as model ensembling, which further improved the final translation performance.",
}
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%0 Conference Proceedings %T NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task %A Li, Zuchao %A Utiyama, Masao %A Sumita, Eiichiro %A Zhao, Hai %Y Nakazawa, Toshiaki %Y Nakayama, Hideki %Y Goto, Isao %Y Mino, Hideya %Y Ding, Chenchen %Y Dabre, Raj %Y Kunchukuttan, Anoop %Y Higashiyama, Shohei %Y Manabe, Hiroshi %Y Pa, Win Pa %Y Parida, Shantipriya %Y Bojar, Ondřej %Y Chu, Chenhui %Y Eriguchi, Akiko %Y Abe, Kaori %Y Oda, Yusuke %Y Sudoh, Katsuhito %Y Kurohashi, Sadao %Y Bhattacharyya, Pushpak %S Proceedings of the 8th Workshop on Asian Translation (WAT2021) %D 2021 %8 August %I Association for Computational Linguistics %C Online %F li-etal-2021-nicts %X This paper describes our system (Team ID: nictrb) for participating in the WAT’21 restricted machine translation task. In our submitted system, we designed a new training approach for restricted machine translation. By sampling from the translation target, we can solve the problem that ordinary training data does not have a restricted vocabulary. With the further help of constrained decoding in the inference phase, we achieved better results than the baseline, confirming the effectiveness of our solution. In addition, we also tried the vanilla and sparse Transformer as the backbone network of the model, as well as model ensembling, which further improved the final translation performance. %R 10.18653/v1/2021.wat-1.4 %U https://aclanthology.org/2021.wat-1.4 %U https://doi.org/10.18653/v1/2021.wat-1.4 %P 62-67
Markdown (Informal)
[NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task](https://aclanthology.org/2021.wat-1.4) (Li et al., WAT 2021)
- NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task (Li et al., WAT 2021)
ACL
- Zuchao Li, Masao Utiyama, Eiichiro Sumita, and Hai Zhao. 2021. NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task. In Proceedings of the 8th Workshop on Asian Translation (WAT2021), pages 62–67, Online. Association for Computational Linguistics.