Speaker identification based oin subtractive clustering algorithm with estimating number of clusters

Abstract

In this paper, we propose a new clustering algorithm that performs clustering the feature vectors for the speaker identification. Unlike typical clustering approaches, the proposed method does the clustering without the initial guesses of locations of the cluster centers and a priori information about the number of clusters. Cluster centers are obtained incrementally by adding one cluster center at a time through the subtractive clustering algorithm. The number of clusters is obtained by investigating the mutual relationship between clusters. The experimental results show the effectiveness of the proposed algorithm as compared with the conventional methods.