Abstract
This study simulates a lexical decision task in Korean by using a feed forward neural network model with a back propagation learning rule. Reaction time is substituted by a entropy value called ‘semantic stress’. The model demonstrates frequency effect, lexical status effect and non-word legality effect, suggesting that lexical decision is made within a structure of orthographic and semantic features. The test implies that the orthographic and semantic features can be automatically applied to lexical information process.
The research presented in the paper is supported by the BK21 grant(H0041800).
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Yim, H., Lim, H., Park, K., Nam, K. (2005). A Computation Model of Korean Lexical Processing. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_114
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DOI: https://doi.org/10.1007/11539087_114
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