Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection

Abstract

In recent years emphasis has been placed upon the early detection of voice pathologies by using the signal processing of voice to evaluate certain time and spectrum domain parameters which may infer the presence of pathology. The present work is aimed at establishing the suitability of these voice spectral parameters in fixing a clear distinction between pathologic and normophonic voice, and to further classify the specific patient's pathology. Principal component analysis is used in parameter selection. Results for normal and pathological samples will be presented and discussed.