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Title:Models of Human Phone Transcription in Noise Based on Intelligibility Predictors
Author(s):Lobdell, Bryce E.
Doctoral Committee Chair(s):Hasegawa-Johnson, Mark A.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Speech Communication
Abstract:The key findings of the experiments are the following: (1) the Articulation Index model recognition accuracy works very well in some phonetic contexts and fails in others, (2) the Articulation Index model is the average of a number of more specific models with their own parameters, (3) audibility of speech does not explain all variation but explains a great deal of it, and (4) phonetic importance is not spread uniformly over the time and frequency. We speculate that humans may use different representations of speech, depending on the phonetic context, and we suggest experiments controlling frequency-band specific signal-to-noise ratio and level to resolve these issues.
Issue Date:2009
Description:174 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.
Other Identifier(s):(MiAaPQ)AAI3363022
Date Available in IDEALS:2015-09-25
Date Deposited:2009

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