Error Detection and Correction Based on Chinese Phonemic Alphabet in Chinese Text

Authors:
Chuen-Min Huang;Mei-Chen Wu;Ching-Che Chang
Affiliations:
Department of Information Management, National Yunlin University of Science & Technology, Taiwan, R.O.C.;Department of Information Management, National Yunlin University of Science & Technology, Taiwan, R.O.C.;Department of Information Management, National Yunlin University of Science & Technology, Taiwan, R.O.C.
Venue:
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Year:
2007

Citing 3
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Abstract

Misspelling and misconception resulting from similar pronunciation appears frequently in Chinese texts. Without double check-up, this situation is getting even worse with the help of Chinese input method editor. It is hoped that the quality of Chinese writing would be enhanced if an effective automatic error detection and correction mechanism embedded in text editor. Therefore, the burden of manpower to proofread shall be released. Until recently, researches on automatic error detection and correction of Chinese text have undergone many challenges and suffered from bad performance compared with that of Western text editor. In view of the prominent phenomenon in Chinese writing problem, this study proposes a learning model based on Chinese phonemic alphabet. The experimental results demonstrate this model is effective in finding out most of words spelled incorrectly, and furthermore this model improves detection and correction rate.