DocumentCode :
431354
Title :
Automatic Dysphonia Recognition using Biologically-Inspired Amplitude-Modulation Features
Author :
Malyska, Nicolas ; Quatieri, Thomas F. ; Sturim, Douglas
Author_Institution :
Lincoln Lab., MIT, Lexington, MA, USA
Volume :
1
fYear :
2005
fDate :
March 18-23, 2005
Firstpage :
873
Lastpage :
876
Keywords :
Gaussian distribution; amplitude modulation; speech processing; speech recognition; AM phenomenon; GMM classification backend; Gaussian-mixture model; Kay elemetrics voice disorders database; automatic dysphonia recognition; band-dependent analysis; biologically inspired amplitude-modulation features; communications engineering; dysphonic speech; glottal source differences; inferior colliculus; larynx phonation; time-varying amplitude fluctuations; Amplitude modulation; Automatic speech recognition; Biological system modeling; Fluctuations; Larynx; Signal analysis; Spectrogram; Speech analysis; Speech recognition; Time domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8874-7
Type :
conf
DOI :
10.1109/ICASSP.2005.1415253
Filename :
1415253
Link To Document :
https://search.ricest.ac.ir/dl/search/defaultta.aspx?DTC=49&DC=431354
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