Support Vector Machines and Wavelets for Voice Disorder Sorting
Rodrigo Capobianco Guido, José Costa Pereira, Everthon Silva Fonseca, Carlos Dias Maciel, L.S. Vieira, Fabrício Lopes Sanchez, M.B.A. Guilerme, Sylvio Barbon · 2006
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.