@inproceedings{wang-etal-2020-casias,
title = "{CASIA}{'}s System for {IWSLT} 2020 Open Domain Translation",
author = "Wang, Qian and
Liu, Yuchen and
Ma, Cong and
Lu, Yu and
Wang, Yining and
Zhou, Long and
Zhao, Yang and
Zhang, Jiajun and
Zong, Chengqing",
editor = {Federico, Marcello and
Waibel, Alex and
Knight, Kevin and
Nakamura, Satoshi and
Ney, Hermann and
Niehues, Jan and
St{\"u}ker, Sebastian and
Wu, Dekai and
Mariani, Joseph and
Yvon, Francois},
booktitle = "Proceedings of the 17th International Conference on Spoken Language Translation",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.iwslt-1.15",
doi = "10.18653/v1/2020.iwslt-1.15",
pages = "130--139",
abstract = "This paper describes the CASIA{'}s system for the IWSLT 2020 open domain translation task. This year we participate in both Chinese→Japanese and Japanese→Chinese translation tasks. Our system is neural machine translation system based on Transformer model. We augment the training data with knowledge distillation and back translation to improve the translation performance. Domain data classification and weighted domain model ensemble are introduced to generate the final translation result. We compare and analyze the performance on development data with different model settings and different data processing techniques.",
}
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<abstract>This paper describes the CASIA’s system for the IWSLT 2020 open domain translation task. This year we participate in both Chinese→Japanese and Japanese→Chinese translation tasks. Our system is neural machine translation system based on Transformer model. We augment the training data with knowledge distillation and back translation to improve the translation performance. Domain data classification and weighted domain model ensemble are introduced to generate the final translation result. We compare and analyze the performance on development data with different model settings and different data processing techniques.</abstract>
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%0 Conference Proceedings
%T CASIA’s System for IWSLT 2020 Open Domain Translation
%A Wang, Qian
%A Liu, Yuchen
%A Ma, Cong
%A Lu, Yu
%A Wang, Yining
%A Zhou, Long
%A Zhao, Yang
%A Zhang, Jiajun
%A Zong, Chengqing
%Y Federico, Marcello
%Y Waibel, Alex
%Y Knight, Kevin
%Y Nakamura, Satoshi
%Y Ney, Hermann
%Y Niehues, Jan
%Y Stüker, Sebastian
%Y Wu, Dekai
%Y Mariani, Joseph
%Y Yvon, Francois
%S Proceedings of the 17th International Conference on Spoken Language Translation
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F wang-etal-2020-casias
%X This paper describes the CASIA’s system for the IWSLT 2020 open domain translation task. This year we participate in both Chinese→Japanese and Japanese→Chinese translation tasks. Our system is neural machine translation system based on Transformer model. We augment the training data with knowledge distillation and back translation to improve the translation performance. Domain data classification and weighted domain model ensemble are introduced to generate the final translation result. We compare and analyze the performance on development data with different model settings and different data processing techniques.
%R 10.18653/v1/2020.iwslt-1.15
%U https://aclanthology.org/2020.iwslt-1.15
%U https://doi.org/10.18653/v1/2020.iwslt-1.15
%P 130-139
Markdown (Informal)
[CASIA’s System for IWSLT 2020 Open Domain Translation](https://aclanthology.org/2020.iwslt-1.15) (Wang et al., IWSLT 2020)
ACL
- Qian Wang, Yuchen Liu, Cong Ma, Yu Lu, Yining Wang, Long Zhou, Yang Zhao, Jiajun Zhang, and Chengqing Zong. 2020. CASIA’s System for IWSLT 2020 Open Domain Translation. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 130–139, Online. Association for Computational Linguistics.