Support vector machine regression for robust speaker verification in mismatching and forensic conditions

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dc.contributor.author Mateos García, Ismael
dc.contributor.author Ramos, Daniel
dc.contributor.author López Moreno, Ignacio
dc.contributor.author González-Rodríguez, Joaquín
dc.contributor.other UAM. Departamento de Ingeniería Informática es_ES
dc.date.accessioned 2015-03-03T17:29:39Z
dc.date.available 2015-03-03T17:29:39Z
dc.date.issued 2009
dc.identifier.citation Advances in Biometrics: Third International Conference, ICB 2009, Alghero, Italy, June 2-5, 2009. Proceedings. Lecture Notes in Computer Science, Volumen 5558. Springer, 2009. 484-493 en_US
dc.identifier.isbn 978-3-642-01792-6 (print) en_US
dc.identifier.isbn 978-3-642-01793-3 (online) en_US
dc.identifier.issn 0302-9743 (print) en_US
dc.identifier.issn 1611-3349 (online) en_US
dc.identifier.uri http://hdl.handle.net/10486/664235
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-01793-3_50 en_US
dc.description Proceedings of Third International Conference, ICB 2009, Alghero, Italy en_US
dc.description.abstract In this paper we propose the use of Support Vector Machine Regression (SVR) for robust speaker verification in two scenarios: i) strong mismatch in speech conditions and ii) forensic environment. The proposed approach seeks robustness to situations where a proper background database is reduced or not present, a situation typical in forensic cases which has been called database mismatch. For the mismatching condition scenario, we use the NIST SRE 2008 core task as a highly variable environment, but with a mostly representative background set coming from past NIST evaluations. For the forensic scenario, we use the Ahumada III database, a public corpus in Spanish coming from real authored forensic cases collected by Spanish Guardia Civil. We show experiments illustrating the robustness of a SVR scheme using a GLDS kernel under strong session variability, even when no session variability is applied, and especially in the forensic scenario, under database mismatch. en_US
dc.description.sponsorship This work has been supported by the Spanish Ministry of Education under project TEC2006-13170-C02-01 en_US
dc.format.extent 11 pág. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Springer Berlin Heidelberg
dc.relation.ispartof Lecture Notes in Computer Science en_US
dc.rights © Springer-Verlag Berlin Heidelberg 2009
dc.subject.other Forensic en_US
dc.subject.other GLDS en_US
dc.subject.other Robustness en_US
dc.subject.other Session variability compensation en_US
dc.subject.other Speaker verification en_US
dc.subject.other SVM classification en_US
dc.subject.other SVM regression en_US
dc.title Support vector machine regression for robust speaker verification in mismatching and forensic conditions en_US
dc.type conferenceObject en
dc.type bookPart en
dc.subject.eciencia Informática es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/978-3-642-01793-3_50
dc.identifier.doi 10.1007/978-3-642-01793-3_50
dc.identifier.publicationfirstpage 484
dc.identifier.publicationlastpage 493
dc.identifier.publicationvolume 5558
dc.relation.eventdate June 2-5, 2009 en_US
dc.relation.eventnumber 3
dc.relation.eventplace Alghero, (Italy) en_US
dc.relation.eventtitle 3rd IAPR/IEEE International Conference on Biometrics, ICB 2009 en_US
dc.type.version info:eu-repo/semantics/acceptedVersion en
dc.contributor.group Análisis y Tratamiento de Voz y Señales Biométricas (ING EPS-002) es_ES
dc.rights.accessRights openAccess en


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