Resolving the unencoded character problem for chinese digital libraries
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the second workshop on Building Educational Applications Using NLP
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
Measuring and predicting orthographic associations: modelling the similarity of Japanese kanji
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Capturing errors in written Chinese words
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Phonological and logographic influences on errors in written Chinese words
ALR7 Proceedings of the 7th Workshop on Asian Language Resources
Visually and phonologically similar characters in incorrect simplified Chinese words
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
ACM Transactions on Asian Language Information Processing (TALIP)
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Chinese characters that are similar in their pronunciations or in their internal structures are useful for computer-assisted language learning and for psycholinguistic studies. Although it is possible for us to employ image-based methods to identify visually similar characters, the resulting computational costs can be very high. We propose methods for identifying visually similar Chinese characters by adopting and extending the basic concepts of a proven Chinese input method--Cangjie. We present the methods, illustrate how they work, and discuss their weakness in this paper.