Person verification by fusion of prosodic, voice spectral and facial parameters

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dc.contributor.author	Hernando, Javier
dc.contributor.author	Farrús, Mireia
dc.contributor.author	Ejarque, Pascual
dc.contributor.author	Garde, Ainara
dc.contributor.author	Luque, Jordi
dc.contributor.author	Comunicació presentada a: SECRYPT 2006, International Conference on Security and Cryptography, celebrada a Setúbal, Portugal, del 7 al 10 d'agost de 2006
dc.date	2006
dc.identifier.citation	Hernando J, Farrús M, Ejarque P, Garde A, Luque J. Person verification by fusion of prosodic, voice spectral and facial parameters. In: Malek M, Fernández-Medina E, Hernando J, editors. SECRYPT 2006, Proceedings of the International Conference on Security and Cryptography; 2006 Aug 7-10; Setúbal, Portugal. [Setubal, Portugal]: INSTICC Press; 2006. p. 17-23. DOI: 10.5220/0002105200170023
dc.identifier.citation	http://dx.doi.org/10.5220/0002105200170023
dc.identifier.uri	http://hdl.handle.net/10230/32160
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	INSTICC Press
dc.relation	Malek M, Fernández-Medina E, Hernando J, editors. SECRYPT 2006, Proceedings of the International Conference on Security and Cryptography; 2006 Aug 7-10; Setúbal, Portugal. [Setubal, Portugal]: INSTICC Press; 2006. p. 17-23.
dc.relation	info:eu-repo/grantAgreement/EC/FP6/506909
dc.relation	info:eu-repo/grantAgreement/EC/FP6/001766
dc.relation	info:eu-repo/grantAgreement/ES/2PN/TIN2005-08852
dc.rights	© SciTePress
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Biometrics
dc.subject	Multimodality
dc.subject	Fusion
dc.subject	Face
dc.subject	Prosody
dc.subject	Support Vector Machines
dc.subject	Matcher weighting
dc.title	Person verification by fusion of prosodic, voice spectral and facial parameters
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/publishedVersion
dc.description.abstract	Prosodic information can be used successfully for automatic speaker recognition, although most of the speaker recognition systems use only short-term spectral features as voice information. In this work, prosody information is added to a multimodal system based on face and voice characteristics in order to improve the performance of the system. Fusion is carried out by using various fusion strategies and two different fusion techniques: support vector machines and matcher weighting. Results are clearly improved when a previous normalization based on histogram equalization is done before the fusion of the monomodal scores.
dc.description.abstract	This work has been partially supported by the European Union (under CHIL IST-2002-506909 and BIOSEC IST-2002-001766) and by the Spanish Government (under ACESCA project TIN2005-08852 and grant AP2003-3598).

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