caa a22 4500 606206175 CHVBK 20210128101010.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00034-014-9927-x doi (NATIONALLICENCE)springer-10.1007/s00034-014-9927-x Voice Disorder Signal Classification Using M-Band Wavelets and Support Vector Machine [Elektronische Daten] [Pouria Saidi, Farshad Almasganj] The aim of this work is to present a noninvasive method to classify normal voice signals and those corresponding to voice disorders. Use of wavelet decomposition is prevalent for feature extraction in this field and provides good frequency resolution in lower-frequency subbands. In this work, to provide better frequency resolution in higher-frequency subbands as well, we use M-band wavelet decomposition for feature extraction, employing a genetic algorithm to determine the parameters of the optimal wavelet. Moreover, a support vector machine is used as the final classifier. By employing a well-known pathological voice database, normal and pathological cases are classified using a five-band wavelet system for feature extraction, showing good performance. Springer Science+Business Media New York, 2015 Voice disorder classification nationallicence M-band wavelets nationallicence Support vector machine nationallicence Genetic algorithm nationallicence Saidi Pouria Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 15875-4413, Tehran, Iran aut Almasganj Farshad Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 15875-4413, Tehran, Iran aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2727-2738 0278-081X 34:8<2727 2015 34 34 https://doi.org/10.1007/s00034-014-9927-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9927-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Saidi Pouria Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 15875-4413, Tehran, Iran aut NATIONALLICENCE 700 1- Almasganj Farshad Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 15875-4413, Tehran, Iran aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2727-2738 0278-081X 34:8<2727 2015 34 34