Speaker verification using combinational features and adaptive neuro-fuzzy inference systems

Authors:
V. Srihari;R. Karthik;R. Anitha;S. D. Suganthi
Affiliations:
PSG College of Technology, Coimbatore, India;PSG College of Technology, Coimbatore, India;PSG College of Technology, Coimbatore, India;PSG College of Technology, Coimbatore, India
Venue:
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Year:
2010

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Abstract

A new efficacious Speaker Verification System is proposed in this paper. Scrutinized study is made on different features and finally a combination of them is used. These combinational features have been modeled with ANFIS and SVM classifier. The performance of both the systems are evaluated with detection error trade-off curves and Bayes Risk function. Results have shown that proposed system using combinational features with ANFIS is more efficient compared to combinational features with SVM classifier.