title: An interactive Hebbian account of lexically guided tuning of speech perception.
abstract: We describe an account of lexically guided tuning of speech perception based on interactive processing and Hebbian learning. Interactive feedback provides lexical information to prelexical levels, and Hebbian learning uses that information to retune the mapping from auditory input to prelexical representations of speech. Simulations of an extension of the TRACE model of speech perception are presented that demonstrate the efficacy of this mechanism. Further simulations show that acoustic similarity can account for the patterns of speaker generalization. This account addresses the role of lexical information in guiding both perception and learning with a single set of principles of information propagation.
authors.affiliation: Department of Psychology, University of Connecticut, 406 Babbidge Rd., Unit 1020, Storrs, CT 06269-1020, USA. daniel.mirman@uconn.edu
authors.forename: Daniel
authors.initials: D
authors.lastname: Mirman
authors.forename: James L
authors.initials: JL
authors.lastname: McClelland
authors.forename: Lori L
authors.initials: LL
authors.lastname: Holt
mesh_terms: D006801:Humans; D007398:Interpersonal Relations; D008962:Models, Theoretical; D010700:Phonetics; D013067:Speech Perception; D014825:Vocabulary