An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study

Keywords: Voice pathology detection, inverse filtering, GMM, UBM

Abstract

An automatic categorization of the speakers according to their sex improves the performance of an automatic detector of voice pathologies. This is grounded on findings demonstrating perceptual, acoustical and anatomical differences in males’ and females’ voices. In particular, this paper follows two objectives: 1) to design a system which automatically discriminates the sex of a speaker when using normophonic and pathological speech, 2) to study the influence that this sex detector has on the accuracy of a further voice pathology detector. The parameterization of the automatic sex detector relies on MFCC applied to speech; and MFCC applied to glottal waveforms plus parameters modeling the vocal tract. The glottal waveforms are extracted from speech via iterative lattice inverse filters. Regarding the pathology detector, a MFCC parameterization is applied to speech signals. Classification, in both sex and pathology detectors, is carried out using state of the art techniques based on universal background models. Experiments are performed in the Saarbrücken database, employing the sustained phonation of vowel /a/. Results indicate that the sex of the speaker may be discriminated automatically using normophonic and pathological speech, obtaining accuracy up to 95%. Moreover, including the a-priori information about the sex of the speaker produces an absolute performance improvement in EER of about 2% on pathology detection tasks.

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Author Biographies

Jorge Andrés Gómez García, Universidad Politécnica de Madrid

Centro de Tecnología Biomédica (CTB)

Laureano Moro Velázquez, Universidad Politécnica de Madrid

Centro de Tecnología Biomédica (CTB)

Juan Ignacio Godino Llorente, Universidad Politécnica de Madrid

Centro de Tecnología Biomédica (CTB)

César Germán Castellanos Domínguez, Universidad Nacional de Colombia

Departamento de Ingeniería Electrónica, Eléctrica y Computación, Sede Manizales

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Published
2016-06-16
How to Cite
Gómez García J. A., Moro Velázquez L., Godino Llorente J. I., & Castellanos Domínguez C. G. (2016). An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study. Revista Facultad De Ingeniería Universidad De Antioquia, (79), 50-62. https://doi.org/10.17533/udea.redin.n79a06