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
- Editors:
- Yuen-Hsien Tseng, Hsin-Hsi Chen, Lung-Hao Lee, Liang-Chih Yu
- Venue:
- NLP-TEA
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 39–44
- Language:
- URL:
- https://aclanthology.org/W17-5907
- DOI:
- Cite (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.
- Cite (Informal):
- N-gram Model for Chinese Grammatical Error Diagnosis (Zhao et al., NLP-TEA 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W17-5907.pdf