Wavelet-FILVQ classifier for speech analysis
G. VandeWouwer, Paul Scheunders, D. VanDyck · 1996
This paper describes a novel speech signal classification scheme based on spectrograms which are subjected to wavelet transform: a procedure which yields specific information regarding time and frequency variation of the signal. Feature vectors are extracted and classified using LVQ networks. The output of the network is interpreted as a fuzzy membership coefficient. This scheme is applied to the classification of voice dysphonia.