An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidad de Antioquia
2016
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| _version_ | 1876454152337358848 |
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| author | Jorge Andrés Gómez-García |
| author_facet | Jorge Andrés Gómez-García |
| contents | An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study Jorge Andrés Gómez-García Laureano Moro-Velázquez Juan Ignacio Godino-Llorente César Germán Castellanos-Domínguez Ingeniería GMM UBM inverse filtering Voice pathology detection 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. 2016 artículo científico 0120-6230 https://www.redalyc.org/articulo.oa?id=43045911006 en http://www.redalyc.org/revista.oa?id=430 Revista Facultad de Ingeniería Universidad de Antioquia application/pdf Universidad de Antioquia Revista Facultad de Ingeniería Universidad de Antioquia (Colombia) Num.79 |
| format | Artículo científico |
| id | redalyc_43045911006 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Universidad de Antioquia |
| spellingShingle | An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study Jorge Andrés Gómez-García Ingeniería GMM UBM inverse filtering Voice pathology detection An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study Jorge Andrés Gómez-García Laureano Moro-Velázquez Juan Ignacio Godino-Llorente César Germán Castellanos-Domínguez Ingeniería GMM UBM inverse filtering Voice pathology detection 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. 2016 artículo científico 0120-6230 https://www.redalyc.org/articulo.oa?id=43045911006 en http://www.redalyc.org/revista.oa?id=430 Revista Facultad de Ingeniería Universidad de Antioquia application/pdf Universidad de Antioquia Revista Facultad de Ingeniería Universidad de Antioquia (Colombia) Num.79 |
| title | An insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study |
| topic | Ingeniería GMM UBM inverse filtering Voice pathology detection |
| url | https://www.redalyc.org/articulo.oa?id=43045911006 |