Reducing the False Alarm Rate of Chinese Character Error Detection and Correction
Shih-Hung Wu, Yongzhi Chen, Ping-Che Yang, Tsun Ku, Chao-Lin Liu · 2010
The main drawback of previous Chinese character error detection systems is the high false alarm rate. To solve this problem, we propose a system that combines a statistic method and template matching to detect Chinese character errors. Error types include pronunciationrelated errors and form-related errors. Possible errors of a character can be collected to form a confusion set. Our system automatically generates templates with the help of a dictionary and confusion sets. The templates can be used to detect and correct errors in essays. In this paper, we compare three methods proposed in previous works. The experiment results show that our system can reduce the false alarm significantly and give the best performance on f-score. 1