Literature DB >> 12132760

Generalizing a neuropsychological model of visual categorization to auditory categorization of vowels.

W Todd Maddox1, Michelle R Molis, Randy L Diehl.   

Abstract

Twelve male listeners categorized 54 synthetic vowel stimuli that varied in second and third formant frequency on a Bark scale into the American English vowel categories [see text]. A neuropsychologically plausible model of categorization in the visual domain, the Striatal Pattern Classifier (SPC; Ashby & Waldron, 1999), is generalized to the auditory domain and applied separately to the data from each observer. Performance of the SPC is compared with that of the successful Normal A Posteriori Probability model (NAPP; Nearey, 1990; Nearey & Hogan, 1986) of auditory categorization. A version of the SPC that assumed piece-wise linear response region partitions provided a better account of the data than the SPC that assumed linear partitions, and was indistinguishable from a version that assumed quadratic response region partitions. A version of the NAPP model that assumed nonlinear response regions was superior to the NAPP model with linear partitions. The best fitting SPC provided a good account of each observer's data but was outperformed by the best fitting NAPP model. Implications for bridging the gap between the domains of visual and auditory categorization are discussed.

Mesh:

Year:  2002        PMID: 12132760     DOI: 10.3758/bf03194728

Source DB:  PubMed          Journal:  Percept Psychophys        ISSN: 0031-5117


  12 in total

1.  Tests of a Dual-systems Model of Speech Category Learning.

Authors:  W Todd Maddox; Bharath Chandrasekaran
Journal:  Biling (Camb Engl)       Date:  2014-10-01

2.  The Role of Corticostriatal Systems in Speech Category Learning.

Authors:  Han-Gyol Yi; W Todd Maddox; Jeanette A Mumford; Bharath Chandrasekaran
Journal:  Cereb Cortex       Date:  2014-10-19       Impact factor: 5.357

3.  Performance Pressure Enhances Speech Learning.

Authors:  W Todd Maddox; Seth Koslov; Han-Gyol Yi; Bharath Chandrasekaran
Journal:  Appl Psycholinguist       Date:  2015-12-23

4.  Perceptual dimensions influence auditory category learning.

Authors:  Casey L Roark; Lori L Holt
Journal:  Atten Percept Psychophys       Date:  2019-05       Impact factor: 2.199

5.  Prior experience with negative spectral correlations promotes information integration during auditory category learning.

Authors:  Mathias Scharinger; Molly J Henry; Jonas Obleser
Journal:  Mem Cognit       Date:  2013-07

6.  What information is necessary for speech categorization? Harnessing variability in the speech signal by integrating cues computed relative to expectations.

Authors:  Bob McMurray; Allard Jongman
Journal:  Psychol Rev       Date:  2011-04       Impact factor: 8.934

7.  Vowel identification by listeners with hearing impairment in response to variation in formant frequencies.

Authors:  Michelle R Molis; Marjorie R Leek
Journal:  J Speech Lang Hear Res       Date:  2011-02-04       Impact factor: 2.297

8.  The role of age and executive function in auditory category learning.

Authors:  Rachel Reetzke; W Todd Maddox; Bharath Chandrasekaran
Journal:  J Exp Child Psychol       Date:  2015-10-22

9.  Dual systems of speech category learning across the lifespan.

Authors:  W Todd Maddox; Bharath Chandrasekaran; Kirsten Smayda; Han-Gyol Yi
Journal:  Psychol Aging       Date:  2013-12

10.  Erasing the engram: the unlearning of procedural skills.

Authors:  Matthew J Crossley; F Gregory Ashby; W Todd Maddox
Journal:  J Exp Psychol Gen       Date:  2012-10-08
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