Automatic Classification of Laryngeal Dysfunction Using the Roots of the Digital Inverse Filter

An automated technique is presented which employs the systems identification properties of the digital inverse filter (IF) [8] for the classification and assessment of laryngeal dysfunction. The information is contained in the positions of the IF polynomial zeros in the complex plane as the IF is computed repeatedly over small analysis segments of a speech sample. A graphic display of the z-plane roots and a vector of pattern features of that display result for each case. The vectors are then processed by an automated clustering procedure to classify the cases in the feature space. The results of the analysis of a large test battery of acoustically degraded synthetic vowel sounds using the IF method are presented.