@inproceedings{zhao-etal-2017-n,
title = "N-gram Model for {C}hinese Grammatical Error Diagnosis",
author = "Zhao, Jianbo and
Liu, Hao and
Bao, Zuyi and
Bai, Xiaopeng and
Li, Si and
Lin, Zhiqing",
editor = "Tseng, Yuen-Hsien and
Chen, Hsin-Hsi and
Lee, Lung-Hao and
Yu, Liang-Chih",
booktitle = "Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications ({NLPTEA} 2017)",
month = dec,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/W17-5907",
pages = "39--44",
abstract = "Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task. The experiment results show that the proposed method is good at correction of Chinese grammatical errors.",
}
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<abstract>Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task. The experiment results show that the proposed method is good at correction of Chinese grammatical errors.</abstract>
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%0 Conference Proceedings
%T N-gram Model for Chinese Grammatical Error Diagnosis
%A Zhao, Jianbo
%A Liu, Hao
%A Bao, Zuyi
%A Bai, Xiaopeng
%A Li, Si
%A Lin, Zhiqing
%Y Tseng, Yuen-Hsien
%Y Chen, Hsin-Hsi
%Y Lee, Lung-Hao
%Y Yu, Liang-Chih
%S Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA 2017)
%D 2017
%8 December
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F zhao-etal-2017-n
%X Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task. The experiment results show that the proposed method is good at correction of Chinese grammatical errors.
%U https://aclanthology.org/W17-5907
%P 39-44
Markdown (Informal)
[N-gram Model for Chinese Grammatical Error Diagnosis](https://aclanthology.org/W17-5907) (Zhao et al., NLP-TEA 2017)
ACL
- Jianbo Zhao, Hao Liu, Zuyi Bao, Xiaopeng Bai, Si Li, and Zhiqing Lin. 2017. N-gram Model for Chinese Grammatical Error Diagnosis. In Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA 2017), pages 39–44, Taipei, Taiwan. Asian Federation of Natural Language Processing.