@inproceedings{zhang-etal-2020-oppos,
title = "{OPPO}{'}s Machine Translation System for the {IWSLT} 2020 Open Domain Translation Task",
author = "Zhang, Qian and
Li, Xiaopu and
Dang, Dawei and
Shi, Tingxun and
Ai, Di and
Xue, Zhengshan and
Hao, Jie",
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-1.13",
doi = "10.18653/v1/2020.iwslt-1.13",
pages = "114--121",
abstract = "In this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on Transformer (Vaswani et al., 2017), with the help of many popular, widely proved effective data preprocessing and augmentation methods. Experiments show that these methods can improve the baseline model steadily and significantly.",
}
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<abstract>In this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on Transformer (Vaswani et al., 2017), with the help of many popular, widely proved effective data preprocessing and augmentation methods. Experiments show that these methods can improve the baseline model steadily and significantly.</abstract>
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%0 Conference Proceedings
%T OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task
%A Zhang, Qian
%A Li, Xiaopu
%A Dang, Dawei
%A Shi, Tingxun
%A Ai, Di
%A Xue, Zhengshan
%A Hao, Jie
%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 zhang-etal-2020-oppos
%X In this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on Transformer (Vaswani et al., 2017), with the help of many popular, widely proved effective data preprocessing and augmentation methods. Experiments show that these methods can improve the baseline model steadily and significantly.
%R 10.18653/v1/2020.iwslt-1.13
%U https://aclanthology.org/2020.iwslt-1.13
%U https://doi.org/10.18653/v1/2020.iwslt-1.13
%P 114-121
Markdown (Informal)
[OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task](https://aclanthology.org/2020.iwslt-1.13) (Zhang et al., IWSLT 2020)
ACL