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Text–Independent Speaker Recognition Using Two–Dimensional Information Entropy Cover

Text–Independent Speaker Recognition Using Two–Dimensional Information Entropy

Open Access
|Jul 2015

Abstract

Speaker recognition is the process of automatically recognizing who is speaking on the basis of speaker specific characteristics included in the speech signal. These speaker specific characteristics are called features. Over the past decades, extensive research has been carried out on various possible speech signal features obtained from signal in time or frequency domain. The objective of this paper is to introduce two-dimensional information entropy as a new text-independent speaker recognition feature. Computations are performed in time domain with real numbers exclusively. Experimental results show that the two-dimensional information entropy is a speaker specific characteristic, useful for speaker recognition.

DOI: https://doi.org/10.2478/jee-2015-0027 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 169 - 173
Submitted on: Feb 26, 2015
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Published on: Jul 14, 2015
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2015 Boško Božilović, Branislav M. Todorović, Miroslav Obradović, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.