Document Detail


Improvement of consonant identification in noise by spectro-temporal enhancement.
MedLine Citation:
PMID:  20330730     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Our previous studies have shown that perception of vowels and consonants in long-term speech-shaped noise (LTSSN) by listeners with normal and impaired hearing is improved significantly by spectro-temporal enhancement resulting from modifications in the spectral modulation domain. The present study manipulated several parameters of enhancement processing including length of the analysis window and size of fast Fourier transform (FFT) analysis to determine which parameters produce the greatest improvement in stop consonant identification in the presence of LTSSN and cafeteria noise for normal-hearing listeners. The speech signals were presented at 70-dB sound pressure level and the signal-to-noise ratio was varied in fixed steps. Results indicated that identification of stop consonants increased by about 10 percentage points in LTSS noise and by about 25 percentage points in cafeteria noise when the length of analysis window was 200 ms and the FFT size was 512 points. Subsequent acoustic analyses showed that such perceptual improvement may be due to enhancement of formant transitions relative to background competition.
Authors:
Chang Liu; David A Eddins
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of the Acoustical Society of America     Volume:  127     ISSN:  1520-8524     ISO Abbreviation:  J. Acoust. Soc. Am.     Publication Date:  2010 Mar 
Date Detail:
Created Date:  2010-03-24     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7503051     Medline TA:  J Acoust Soc Am     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1904     Citation Subset:  IM    
Affiliation:
Dept. of Commun. Sci. and Disorder, 1 Univ. Station A1100, The Univ. of Texas at Austin, Austin, TX 78712Univ. of Rochester, Rochester, NY 14642 and Rochester Inst. of Technol., Rochester, NY 14623.
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