OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task

Qian Zhang; Xiaopu Li; Dawei Dang; Tingxun Shi; Di Ai; Zhengshan Xue; Jie Hao

doi:10.18653/v1/2020.iwslt-1.13

OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task

Qian Zhang, Xiaopu Li, Dawei Dang, Tingxun Shi, Di Ai, Zhengshan Xue, Jie Hao

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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.

Anthology ID:: 2020.iwslt-1.13
Volume:: Proceedings of the 17th International Conference on Spoken Language Translation
Month:: July
Year:: 2020
Address:: Online
Editors:: Marcello Federico, Alex Waibel, Kevin Knight, Satoshi Nakamura, Hermann Ney, Jan Niehues, Sebastian Stüker, Dekai Wu, Joseph Mariani, Francois Yvon
Venue:: IWSLT
SIG:: SIGSLT
Publisher:: Association for Computational Linguistics
Note:
Pages:: 114–121
Language:
URL:: https://aclanthology.org/2020.iwslt-1.13/
DOI:: 10.18653/v1/2020.iwslt-1.13
Bibkey:
Cite (ACL):: Qian Zhang, Xiaopu Li, Dawei Dang, Tingxun Shi, Di Ai, Zhengshan Xue, and Jie Hao. 2020. OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 114–121, Online. Association for Computational Linguistics.
Cite (Informal):: OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task (Zhang et al., IWSLT 2020)
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PDF:: https://aclanthology.org/2020.iwslt-1.13.pdf
Video:: http://slideslive.com/38929611

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Endnote
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@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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%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

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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)

OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task (Zhang et al., IWSLT 2020)

ACL

Qian Zhang, Xiaopu Li, Dawei Dang, Tingxun Shi, Di Ai, Zhengshan Xue, and Jie Hao. 2020. OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 114–121, Online. Association for Computational Linguistics.