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Arsalane Zarghili
University Sidi Mohamed Ben Abdellah Fez, Morocco.
Computer Science & IT Electrical & Electronics Engineering

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Towards an Optimal Speaker Modeling in Speaker Verification Systems using Personalized Background Models Ayoub Bouziane; Jamal Kharroubi; Arsalane Zarghili
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1669.57 KB) | DOI: 10.11591/ijece.v7i6.pp3655-3663

Abstract

This paper presents a novel speaker modeling approachfor speaker recognition systems. The basic idea of this approach consists of deriving the target speaker model from a personalized background model, composed only of the UBM Gaussian components which are really present in the speech of the target speaker. The motivation behind the derivation of speakers’ models from personalized background models is to exploit the observeddifference insome acoustic-classes between speakers, in order to improve the performance of speaker recognition systems.The proposed approach was evaluatedfor speaker verification task using various amounts of training and testing speech data. The experimental results showed that the proposed approach is efficientin termsof both verification performance and computational cost during the testing phase of the system, compared to the traditional UBM based speaker recognition systems.
Co-Authors Ayoub Bouziane Jamal Kharroubi