Document Detail


Log-linear modeling of consonant confusion data.
MedLine Citation:
PMID:  3950205     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Log-linear models, in conjunction with the G2 statistic, were developed and applied to several existing sets of consonant confusion data. Significant interactions of consonant error patterns were found with signal-to-noise ratio (S/N), presentation level, vowel context, and low-pass and high-pass filtering. These variables also showed significant interactions with error patterns when categorized on the basis of feature classifications. Patterns of errors were significantly altered by S/N for place of articulation (front, middle, back), voicing, frication, and nasality. Low-pass filtering significantly affected error patterns when categorized by place of articulation, duration, or nasality; whereas, high-pass filtering only affected voicing and frication error patterns. This paper also demonstrates the utility of log-linear modeling techniques in applications to confusion matrix analysis: specific effects can be tested; variant cells in a matrix can be isolated with respect to a particular model of interest; diagonal cells can be eliminated from the analysis; and the matrix can be collapsed across levels of variables, with no violation of independence. Finally, log-linear techniques are suggested for development of parsimonious and predictive models of speech perception.
Authors:
T S Bell; D D Dirks; H Levitt; J R Dubno
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  The Journal of the Acoustical Society of America     Volume:  79     ISSN:  0001-4966     ISO Abbreviation:  J. Acoust. Soc. Am.     Publication Date:  1986 Feb 
Date Detail:
Created Date:  1986-04-17     Completed Date:  1986-04-17     Revised Date:  2006-12-27    
Medline Journal Info:
Nlm Unique ID:  7503051     Medline TA:  J Acoust Soc Am     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  518-25     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Humans
Phonetics*
Psychoacoustics
Speech Perception*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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