Using Dysphonic Voice to Characterize Speaker’s Biometry
Phonation distortion leaves relevant marks in a speaker’s biometricpro le. Dysphonic voice production may be used for biometrical speaker charac-terization. In the present paper phonation features derived from the glottal source(GS) parameterization, after vocal tract inversion, is proposed for dysp...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/362907 |
| Acceso en línea: | http://hdl.handle.net/10261/362907 |
| Access Level: | acceso abierto |
| Palabra clave: | Phonation Speaker Recognition Voice Production Speech Processing Linguistic research |
| Sumario: | Phonation distortion leaves relevant marks in a speaker’s biometricpro le. Dysphonic voice production may be used for biometrical speaker charac-terization. In the present paper phonation features derived from the glottal source(GS) parameterization, after vocal tract inversion, is proposed for dysphonic voicecharacterization in Speaker Veri cation tasks. The glottal source derived param-eters are matched in a forensic evaluation framework de ning a distance-basedmetric speci cation. The phonation segments used in the study are derived from llers, long vowels, and other phonation segments produced in spontaneous tele-phone conversations. Phonated segments from a telephonic database of 100 maleSpanish native speakers are combined in a 10-fold cross-validation task to producethe set of quality measurements outlined in the paper. Shimmer, mucosal wavecorrelate, vocal fold cover biomechanical parameter unbalance and a subset of theGS cepstral pro le produce accuracy rates as high as 99.57 for a wide threshold in-terval (62.08-75.04%). An Equal Error Rate of 0.64 % can be granted. The proposedmetric framework is shown to behave more fairly than classical likelihood ratiosin supporting the hypothesis of the defense vs that of the prosecution, thus offeringa more reliable evaluation scoring. Possible applications are Speaker Veri cationand Dysphonic Voice Grading |
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