Support vector machines and wavelets for voice disorder sorting

Author

Guido, R.C. ; Pereira, Jose Casimiro ; Fonseca, E.S. ; Maciel, C.D. ; Vieira, L.S. ; Guilerme, F.L.S.M.B.A. ; Barbon, Sylvio

Author_Institution

Dept. of Phys. & Inf., Sao Paulo Univ.

fYear

2006

Firstpage

434

Lastpage

438

Abstract

We present an algorithm to distinguish between pathological and normal human voice signals based on discrete wavelet transforms (DWT) and support vector machines (SVM). The former is used for time-frequency analysis and provides quantitative evaluation of signal characteristics. The latter is used for the final classification. The technique leads to an adequate larynx pathology classifier with over 95% of classification accuracy

Keywords

acoustic signal processing; discrete wavelet transforms; support vector machines; time-frequency analysis; discrete wavelet transforms; larynx pathology classifier; support vector machines; time-frequency analysis; voice disorder sorting; Discrete wavelet transforms; Human voice; Multiresolution analysis; Pathology; Physics; Sorting; Support vector machine classification; Support vector machines; Time frequency analysis; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, 2006. SSST '06. Proceeding of the Thirty-Eighth Southeastern Symposium on

Conference_Location

Cookeville, TN

Print_ISBN

0-7803-9457-7

Type

conf

DOI

10.1109/SSST.2006.1619117

Filename

1619117

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1657280