@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",
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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<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.</abstract>
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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
%S Proceedings of the 8th Workshop on Asian Translation (WAT2021)
%D 2021
%8 aug
%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)
ACL