Improving the performance of speech clustering methods using I-vectors

Abstract

Abstract Identification of speaker for the speech segment is a challenging task in speech clustering. Similar segments (i.e., those segments are spoken by the same speaker) are grouped into a cluster. Thus, segment labelling is very important in speaker detection. Existing systems use the Gaussian mixture model (GMM) for deriving the GMM mean supervector of speech segments in segment labelling process. i-vectors are tougher than GMM mean supervectors and i-vectors are between GMM mean supervectors high-dimensional space and low-dimensional manifolds. Existing GMM based speech clustering method is modified by i-vectors for achieving an effective speech clustering method. In order to show the feasibility of the proposed work, Experiments are performed on real time speech datasets.