DocumentCode :
3116097
Title :
Pathological Voice Assessment
Author :
Dibazar, Alireza A. ; Berger, Theodore W. ; Narayanan, Shrikanth S.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
1669
Lastpage :
1673
Abstract :
While there are number of guidelines and methods used in practice, there is no standard universally agreed upon system for assessment of pathological voices. Pathological voices are primarily labeled based on the perceptual judgments of specialists, a process that may result in different label(s) being assigned to a given voice sample. This paper focuses on the recognition of five specific pathologies. The main goal is to compare two different classification methods. The first method considers single label classification by assigning a new label (single label) to the ensembles to which they most likely belong. The second method employs all labels originally assigned to the voice samples. Our results show that the pathological voice assessment performance in the second method is improved with respect to the first method
Keywords :
cepstral analysis; diseases; hidden Markov models; maximum likelihood estimation; pattern classification; speech recognition; Mel frequency cepstral coefficients; anterior-posterior squeezing; classification methods; gastric reflux; hidden Markov model; hyper-function; maximum a posteriori estimation; multiclass recognition; paralysis; pathological voice assessment; pathology recognition; perceptual judgment; single label classification; speech analysis; ventricular compression; Acoustic measurements; Biomedical engineering; Biomedical measurements; Cities and towns; Electric variables measurement; Frequency measurement; Laboratories; Pathology; Speech analysis; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.259835
Filename :
4462091
Link To Document :
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