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A Temporal Fuzzy-ART Neural Network Architecture as a Model of Phoneme Perception

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/13093

A Temporal Fuzzy-ART Neural Network Architecture as a Model of Phoneme Perception

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dc.contributor.author Hjelm, Rex Devon
dc.date.accessioned 2011-08-30T18:13:37Z
dc.date.available 2011-08-30T18:13:37Z
dc.date.issued 2011-08-30
dc.date.submitted July 2011
dc.identifier.uri http://hdl.handle.net/1928/13093
dc.description.abstract This paper explores the applicability of Adaptive Resistance Theory- (ART-) type neural networks for finding and encoding linguistic structures, specifically those corresponding to acoustic patterns in natural speech. We build an interpretation of human perceptual response to acoustic pattern in natural speech, translating this to a neural architecture as a model of acquisition, storage, and classification of acoustic speech patterns. en_US
dc.language.iso en_US en_US
dc.subject Phoneme Perception Neural Networks Pattern Recognition en_US
dc.subject.lcsh Phonemic awareness
dc.subject.lcsh Phonetics, Acoustic
dc.subject.lcsh Speech perception
dc.subject.lcsh Neural networks (Neurobiology)
dc.subject.lcsh Pattern perception
dc.title A Temporal Fuzzy-ART Neural Network Architecture as a Model of Phoneme Perception en_US
dc.type Thesis en_US
dc.description.degree Linguistics en_US
dc.description.level Masters en_US
dc.description.department University of New Mexico. Dept. of Linguistics en_US
dc.description.advisor Luger, George
dc.description.committee-member Morford, Jill
dc.description.committee-member Caudell, Thomas


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