University of Hertfordshire

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Efficient speaker change detection using adapted Gaussian mixture models

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Original languageEnglish
Pages (from-to)1859-1869
JournalIEEE Transactions on Audio, Speech and Language Processing
Journal publication date2007
Volume15
Issue6
DOIs
Publication statusPublished - 2007

Abstract

A new approach to speaker change detection is proposed and investigated. The method, which is based on a probabilistic framework, provides an effective means for tackling the problem posed by phonetic variation in high-resolution speaker change detection. Additionally, the approach incorporates the capability for dealing with undesired effects of variations in speech characteristics. Using the experimental investigations conduced with clean and broadcast news audio, it is shown that the proposed method is significantly more effective than the currently popular techniques for speaker change detection. To enhance the computational efficiency of the proposed method, modified implementation algorithms are introduced which are based on the exploitation of the redundant operations and a fast scoring procedure. It is shown that, through the use of the proposed fast algorithm, the computational efficiency of the approach can be increased by over 77% without significant reduction in its accuracy. The paper discusses the principles and characteristics of the proposed speaker change detection method, and provides a detailed description of its efficient implementation. The experiments, investigating the performance of the proposed method and its effectiveness in relation to other approaches, are described and an analysis of the results is presented.

Notes

Original article can be found at: http://ieeexplore.ieee.org/xpl/RecentIssue.jsppunumber=10376-- This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.-- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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