Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients FeaturesReport as inadecuate




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Computational and Mathematical Methods in Medicine - Volume 2015 2015, Article ID 956249, 12 pages -

Research Article

Department of Electrical Electronics Engineering, Bursa Orhangazi University, 16310 Bursa, Turkey

Department of Computer Engineering, Bursa Orhangazi University, 16310 Bursa, Turkey

Received 18 June 2015; Revised 27 October 2015; Accepted 28 October 2015

Academic Editor: Valeri Makarov

Copyright © 2015 Ömer Eskidere and Ahmet Gürhanlı. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The Mel Frequency Cepstral Coefficients MFCCs are widely used in order to extract essential information from a voice signal and became a popular feature extractor used in audio processing. However, MFCC features are usually calculated from a single window taper characterized by large variance. This study shows investigations on reducing variance for the classification of two different voice qualities normal voice and disordered voice using multitaper MFCC features. We also compare their performance by newly proposed windowing techniques and conventional single-taper technique. The results demonstrate that adapted weighted Thomson multitaper method could distinguish between normal voice and disordered voice better than the results done by the conventional single-taper Hamming window technique and two newly proposed windowing methods. The multitaper MFCC features may be helpful in identifying voices at risk for a real pathology that has to be proven later.





Author: Ömer Eskidere and Ahmet Gürhanlı

Source: https://www.hindawi.com/



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