Abstract
A collection of 3208 reported errors of Chinese words were analyzed. Among which, 7.2% involved rarely used character, and 98.4% were assigned common classifications of their causes by human subjects. In particular, 80% of the errors observed in writings of middle school students were related to the pronunciations and 30% were related to the compositions of words. Experimental results show that using intuitive Web-based statistics helped us capture only about 75% of these errors. In a related task, the Web-based statistics are useful for recommending incorrect characters for composing test items for "incorrect character identification" tests about 93% of the time. © 2009 ACL and AFNLP.
Cite
CITATION STYLE
Liu, C. L., Tien, K. W., Lai, M. H., Chuang, Y. H., & Wu, S. H. (2009). Capturing errors in written Chinese words. In ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf. (pp. 25–28). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1667583.1667593
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