Title :
A novel voice signal discrimination algorithm and its application
Author :
Wei, Yu ; Qiang, Han ; Hosseini, Hamid Gholam ; Cameron, Andrew
Author_Institution :
Fac. of Commun. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
A new algorithm which is capable of classifying voice signals recorded from subjects before and after the anesthetic procedure is presented. This new algorithm is based on Wavelet Packet Analysis (WPA) and Least Squares Support Vector Machines (LSSVM) and it combines the coefficients of WPA with other parameters, such as Spectral Centroid, Spectral roll-off point etc., as the feature vector. Experimental evaluation has shown that the proposed classification algorithm based on WPA and LSSVM is very effective as compared to the other two methods, and the total accuracy rate is over 85%.
Keywords :
audio recording; least squares approximations; signal classification; support vector machines; wavelet transforms; LSSVM; WPA; anesthetic procedure; least square support vector machine; spectral centroid; spectral roll-off point; voice signal classification; voice signal discrimination algorithm; voice signal recording; wavelet packet analysis; Accuracy; Classification algorithms; Feature extraction; Speech; Support vector machines; Wavelet packets; Feature Selection; Least Squares Support Vector Machines; Wavelet Packet Analysis;
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
DOI :
10.1109/MSNA.2012.6324540
