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  4. Person identification using face and speech

Person identification using face and speech

Files

201011032.pdf (1.43 MB)

Date

2012

Authors

Parmar, Ajay

Journal Title

Journal ISSN

Volume Title

Publisher

Dhirubhai Ambani Institute of Information and Communication Technology

Abstract

In 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

Description

Keywords

Human face recognition, Biometric identification, Speaker, Emotion Recognition System, Speaker Recognition, Automatic Speech Recognition System, Multimodal Integration, Audio-visual recognition, Person identification

Citation

Parmar, Ajay (2012). Person identification using face and speech. Dhirubhai Ambani Institute of Information and Communication Technology, viii, 26 p. (Acc.No: T00363)

URI

http://ir.daiict.ac.in/handle/123456789/400

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M Tech Dissertations

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