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          Institute: MPI für Psycholinguistik     Collection: Decoding Continuous Speech     Display Documents



ID: 372000.0, MPI für Psycholinguistik / Decoding Continuous Speech
Shortlist B: A Bayesian model of continuous speech recognition
Authors:Norris, Dennis; McQueen, James M.
Language:English
Date of Publication (YYYY-MM-DD):2008
Title of Journal:Psychological Review
Volume:115
Issue / Number:2
Start Page:357
End Page:395
Review Status:not specified
Audience:Experts Only
Abstract / Description:A Bayesian model of continuous speech recognition is presented. It is based on Shortlist ( D. Norris, 1994; D. Norris, J. M. McQueen, A. Cutler, & S. Butterfield, 1997) and shares many of its key assumptions: parallel competitive evaluation of multiple lexical hypotheses, phonologically abstract prelexical and lexical representations, a feedforward architecture with no online feedback, and a lexical segmentation algorithm based on the viability of chunks of the input as possible words. Shortlist B is radically different from its predecessor in two respects. First, whereas Shortlist was a connectionist model based on interactive-activation principles, Shortlist B is based on Bayesian principles. Second, the input to Shortlist B is no longer a sequence of discrete phonemes; it is a sequence of multiple phoneme probabilities over 3 time slices per segment, derived from the performance of listeners in a large-scale gating study. Simulations are presented showing that the model can account for key findings: data on the segmentation of continuous speech, word frequency effects, the effects of mispronunciations on word recognition, and evidence on lexical involvement in phonemic decision making. The success of Shortlist B suggests that listeners make optimal Bayesian decisions during spoken-word recognition.
External Publication Status:published
Document Type:Article
Communicated by:James McQueen
Affiliations:MPI für Psycholinguistik
Identifiers:DOI:10.1037/0033-295X.115.2.357
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