A novel voice signal discrimination algorithm and its application
Wei Yu, Han Qiang, Hamid GholamHosseini, Andrew Cameron · 2012
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%.