Abstract
The Glottal Source is an important component of voice as it can be considered as the excitation signal to the voice apparatus. The use of the Glottal Source for pathology detection or the biometric characterization of the speaker are important objectives in the acoustic study of the voice nowadays. Through the present work a biometric signature based on the speaker’s power spectral density of the Glottal Source is presented. It may be shown that this spectral density is related to the vocal fold cover biomechanics, and from literature it is well-known that certain speaker’s features as gender, age or pathologic condition leave changes in it. The paper describes the methodology to estimate the biometric signature from the power spectral density of the mucosal wave correlate, which after normalization can be used in pathology detection experiments. Linear Discriminant Analysis is used to confront the detection capability of the parameters defined on this glottal signature among themselves and compared to classical perturbation parameters. A database of 100 normal and 100 pathologic subjects equally balanced in gender and age is used to derive the best parameter cocktails for pathology detection and quantification purposes to validate this methodology in voice evaluation tests. In a study case presented to illustrate the detection capability of the methodology exposed a control subset of 24 + 24 subjects is used to determine a subject’s voice condition in a pre- and post-surgical evaluation. Possible applications of the study can be found in pathology detection and grading and in rehabilitation assessment after treatment.
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