@inproceedings{su-etal-2017-rephrasing,
title = "Rephrasing Profanity in {C}hinese Text",
author = "Su, Hui-Po and
Huang, Zhen-Jie and
Chang, Hao-Tsung and
Lin, Chuan-Jie",
editor = "Waseem, Zeerak and
Chung, Wendy Hui Kyong and
Hovy, Dirk and
Tetreault, Joel",
booktitle = "Proceedings of the First Workshop on Abusive Language Online",
month = aug,
year = "2017",
address = "Vancouver, BC, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-3003",
doi = "10.18653/v1/W17-3003",
pages = "18--24",
abstract = "This paper proposes a system that can detect and rephrase profanity in Chinese text. Rather than just masking detected profanity, we want to revise the input sentence by using inoffensive words while keeping their original meanings. 29 of such rephrasing rules were invented after observing sentences on real-word social websites. The overall accuracy of the proposed system is 85.56{\%}",
}
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<abstract>This paper proposes a system that can detect and rephrase profanity in Chinese text. Rather than just masking detected profanity, we want to revise the input sentence by using inoffensive words while keeping their original meanings. 29 of such rephrasing rules were invented after observing sentences on real-word social websites. The overall accuracy of the proposed system is 85.56%</abstract>
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%0 Conference Proceedings
%T Rephrasing Profanity in Chinese Text
%A Su, Hui-Po
%A Huang, Zhen-Jie
%A Chang, Hao-Tsung
%A Lin, Chuan-Jie
%Y Waseem, Zeerak
%Y Chung, Wendy Hui Kyong
%Y Hovy, Dirk
%Y Tetreault, Joel
%S Proceedings of the First Workshop on Abusive Language Online
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, BC, Canada
%F su-etal-2017-rephrasing
%X This paper proposes a system that can detect and rephrase profanity in Chinese text. Rather than just masking detected profanity, we want to revise the input sentence by using inoffensive words while keeping their original meanings. 29 of such rephrasing rules were invented after observing sentences on real-word social websites. The overall accuracy of the proposed system is 85.56%
%R 10.18653/v1/W17-3003
%U https://aclanthology.org/W17-3003
%U https://doi.org/10.18653/v1/W17-3003
%P 18-24
Markdown (Informal)
[Rephrasing Profanity in Chinese Text](https://aclanthology.org/W17-3003) (Su et al., ALW 2017)
ACL
- Hui-Po Su, Zhen-Jie Huang, Hao-Tsung Chang, and Chuan-Jie Lin. 2017. Rephrasing Profanity in Chinese Text. In Proceedings of the First Workshop on Abusive Language Online, pages 18–24, Vancouver, BC, Canada. Association for Computational Linguistics.