Improving the performance of speech clustering methods using I-vectors. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Suneetha Rani, R; Prasad, G LV; Prakash, A; Ramesh, A
• Is Part Of: IOP conference series. Volume 1070:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Speech clustering -- GMM -- GMM mean supervectors -- i-vectors.; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1070/1/012066
• Languages: English
• ISSNs: 1757-8981

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.