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Title:Incremental lexical learning in speech production: a computational model and empirical evaluation
Author(s):Oppenheim, Gary M.
Director of Research:Dell, Gary S.
Doctoral Committee Chair(s):Dell, Gary S.
Doctoral Committee Member(s):Bock, J. Kathryn; Cohen, Neal C.; Hummel, John E.; Ross, Brian H.
Department / Program:Psychology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):lexical access
incremental learning
neural network model
language production
speech production
word retrieval
Abstract:Naming a picture of a dog primes the subsequent naming of a picture of a dog (repetition priming) and interferes with the subsequent naming of a picture of a cat (semantic interference). Behavioral studies suggest that these effects derive from persistent changes in the way that words are activated and selected for production, and some have claimed that the findings are only understandable by positing a competitive mechanism for lexical selection. This dissertation presents and evaluates a simple model of lexical retrieval in speech production that applies error-driven learning to its lexical activation network. This model naturally produces repetition priming and semantic interference effects. It predicts the major findings from several published experiments, demonstrating that these effects may arise from incremental learning. Furthermore, analysis of the model suggests that competition during lexical selection is not necessary for semantic interference if the learning process is itself competitive. Three additional experiments seek to evaluate the temporal persistence of semantic interference effects, as predicted by an incremental learning account.
Issue Date:2012-02-06
Rights Information:Copyright 2011 Gary M. Oppenheim
Date Available in IDEALS:2012-02-06
Date Deposited:2011-12

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