Multispectral Analysis of Diplophonic Voices using Wavelets as a Preprocessing Tool

S.A. Bentil and Y. Yan (USA)


Vocal quality, voice characterization wavelet transform, spectrogram


We present a method to quantitatively characterize voice abnormalities using wavelet analysis as a preprocessing step. The proposed method uses wavelets to decompose acoustic and electroglottography (EGG) signals, acquired clinically from patients with normal and pathological voices, into their designated frequency/time components. These components contain valuable information on the unique dynamic properties of the vocal system and we can correlate these properties with specific voice conditions. A comparative analysis of the vocal signals acquired from a patient suffering from muscular tension dysphonia (MTD) before and after treatment using spectrogram and FFT is also presented. These combined analyses provide a comprehensive representation and quantitative characteristics of the vocal dynamics, which may provide key indication of vocal abnormalities.

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