JCOM_V3_N3_RP4 Piyush Mishra Piyush Lotia Journal on Computer Science 2347–6141 3 3 23 27 Polynomial Kernel, Dynamic Time Warping, Confusion Matrix, Support Vector Machine (SVM), Classifier, Accuracy, Precision In this paper, the authors have presented an efficient algorithm for improving the performance of speaker verification system by using polynomial kernel support vector machine along with dynamic time warping. The objective of speaker verification is to verify the identity of the speaker by characterizing the information of speaker. The idea is to improve the accuracy of Support Vector Machine (SVM) classifier with the combination of dynamic time warping and polynomial kernel. The resultant of SVM has higher degree of precision as well as accuracy. To characterize the classification accuracy and precision, we use a technique called as confusion matrix. The authors have performed the experiment over database of 30 speakers including male and female voices. The polynomial kernel SVM is used here to improve the accuracy. September - November 2015 Copyright © 2015 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3662