Person identification using face and speech

dc.accession.numberT00363
dc.classification.ddc006.4 PAR
dc.contributor.advisorJoshi, Manjunath V.
dc.contributor.authorParmar, Ajay
dc.date.accessioned2017-06-10T14:39:58Z
dc.date.accessioned2025-06-28T10:20:55Z
dc.date.available2017-06-10T14:39:58Z
dc.date.issued2012
dc.degreeM. Tech
dc.description.abstractIn this thesis, we present a multimodal biometric system using face and speech features. Multimodal biometrics system uses two or more intrinsic physical or behaviour traits to provide better recognition rate than unimodal biometric systems. Face recognition is built using principal component analysis (PCA) and the Gabor filters. In Face recognition, PCA is applied to Gabor filter bank response of the face images. Speaker recognition is built using amplitude modulation - frequency modulation (AM-FM) features. AM-FM features are weighted-instantaneous frequency of the analytical signal. Finally, weighted sum of score of face and speaker recognition system is used for person identification. Performance of our system is evaluated by using ORL database for face images and ELSDSR database for speech. Experimental results show better recognition rate for the multimodal sytem when compared to unimodal system
dc.identifier.citationParmar, Ajay (2012). Person identification using face and speech. Dhirubhai Ambani Institute of Information and Communication Technology, viii, 26 p. (Acc.No: T00363)
dc.identifier.urihttp://drsr.daiict.ac.in/handle/123456789/400
dc.publisherDhirubhai Ambani Institute of Information and Communication Technology
dc.student.id201011032
dc.subjectHuman face recognition
dc.subjectBiometric identification
dc.subjectSpeaker
dc.subjectEmotion Recognition System
dc.subjectSpeaker Recognition
dc.subjectAutomatic Speech Recognition System
dc.subjectMultimodal Integration
dc.subjectAudio-visual recognition
dc.subjectPerson identification
dc.titlePerson identification using face and speech
dc.typeDissertation

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