The kappa statistic: a second look
Computational Linguistics
ElectricDict '04 Proceedings of the Workshop on Enhancing and Using Electronic Dictionaries
Kansuke: A logograph look-up interface based on a few modified stroke prototypes
ACM Transactions on Computer-Human Interaction (TOCHI)
Orthographic similarity search for dictionary lookup of Japanese words
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Measuring and predicting orthographic associations: modelling the similarity of Japanese kanji
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
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Japanese kanji recognition experiments are typically narrowly focused, and feature only native speakers as participants. It remains unclear how to apply their results to kanji similarity applications, especially when learners are much more likely to make similarity-based confusion errors. We describe an experiment to collect authentic human similarity judgements from participants of all levels of Japanese proficiency, from non-speaker to native. The data was used to construct simple similarity models for kanji based on pixel difference and radical cosine similarity, in order to work towards genuine confusability data. The latter model proved the best predictor of human responses.