ICNC 2005: Advances in Natural Computation pp 844-849 | Cite as
A Computation Model of Korean Lexical Processing
Conference paper
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.
Keywords
Lexical Decision Lexical Decision Task Lexical Access Semantic Feature Input Structure
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer-Verlag Berlin Heidelberg 2005