A computational Korean lexical access model using artificial neural network

Heui Seok Lim, Kichun Nam, Kinam Park, Sungho Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a computational Korean lexical access model based on connectionist approach. The model is designed to simulate the behaviors observed in human lexical decision task. The proposed model adopts a simple recurrent neural network architecture which takes a Korean string of 2-syllable length as an input and makes an output as a semantic vector representing semantic of the input. As experimental results, the model shows similar behaviors of human lexical decision task such as frequency effect, lexical status effect, word similarity effect, semantic priming effect, and visual degradation effect.

Original languageEnglish
Title of host publicationComputational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings
PublisherSpringer Verlag
Pages693-701
Number of pages9
ISBN (Print)3540372776, 9783540372776
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventInternational Conference on Intelligent Computing, ICIC 2006 - Kunming, China
Duration: 2006 Aug 162006 Aug 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4115 LNBI -III
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Intelligent Computing, ICIC 2006
Country/TerritoryChina
CityKunming
Period06/8/1606/8/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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