Speaker verification using combinational features and adaptive neuro-fuzzy inference systems
V. Srihari, R. M. Karthik, R. Anitha, S. Suganthi · 2010
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.