N-gram Model for Chinese Grammatical Error Diagnosis

Jianbo Zhao, Hao Liu, Zuyi Bao, Xiaopeng Bai, Si Li, Zhiqing Lin


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.
Anthology ID:
W17-5907
Volume:
Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA 2017)
Month:
December
Year:
2017
Address:
Taipei, Taiwan
Venues:
NLP-TEA | WS
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
39–44
Language:
URL:
https://www.aclweb.org/anthology/W17-5907
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-5907.pdf