%0 Journal Article %A Ghoraani, Behnaz %A Umapathy, Karthikeyan %A Sugavaneswaran, Lakshmi %A Krishnan, Sridhar %D 2012 %I Begell House %K pathological speech detection, voice quality assessment, feature extraction, classification, time-frequency features %N 1 %P 63-95 %R 10.1615/CritRevBiomedEng.v40.i1.40 %T Pathological Speech Signal Analysis Using Time-Frequency Approaches %U https://www.dl.begellhouse.com/journals/4b27cbfc562e21b8,26374fd93344680e,18fe9d4d0d499904.html %V 40 %X Acoustical measures of vocal function are important in the assessments of disordered voice, and for monitoring patients' progress over the course of voice therapy. In the last 2 decades, a variety of techniques for automatic pathological voice detection have been proposed, ranging from traditional temporal or spectral approaches to advanced time-frequency techniques. However, comparison of these methods is a difficult task because of the diversity of approaches. In this article, we explain a framework that holds the existing methods. In the light of this framework, the methodologic principles of disordered voice analysis schemes are compared and discussed. In addition, this article presents a comprehensive review to demonstrate the advantages of time-frequency approaches in analyzing and extracting pathological structures from speech signals. This information may have an important role in the development of new approaches to this problem. %8 2012-03-16