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Wavelet-FILVQ classifier for speech analysis

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3 Author(s)
VandeWouwer, G. ; Vision Lab., Antwerp Univ. ; Scheunders, P. ; VanDyck, D.

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

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996

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