title: Pathological speech signal analysis using time-frequency approaches.
abstract: 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.
authors.affiliation: Ryerson University, Toronto, Ontario, Canada.
authors.forename: Behnaz
authors.initials: B
authors.lastname: Ghoraani
authors.forename: Karthikeyan
authors.initials: K
authors.lastname: Umapathy
authors.forename: Lakshmi
authors.initials: L
authors.lastname: Sugavaneswaran
authors.forename: Sridhar
authors.initials: S
authors.lastname: Krishnan
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013018:Sound Spectrography / Q000379:methods*; D013064:Speech Disorders / Q000175:diagnosis*; D013068:Speech Production Measurement / Q000379:methods*