Comparison of automated and perceptual categorization of normal and pathological voices

Virgilijus Uloza, Antanas Verikas, Adas Gelzinis, Marija Bacauskiene & Marius Kaseta
Introduction: The aim of the present study was to evaluate the accuracy of the elaborated automated voice categorization system when classifying voice signal samples into the healthy and pathological classes and to compare it with the classification accuracy attained by human experts. Methods: Effectiveness[for full text, please go to the a.m. URL]