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Reseach Article

Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram

by Prachi J. Natu, Shachi J. Natu, Dr. T. K. Sarode, Dr. H. B. Kekre
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 6
Year of Publication: 2010
Authors: Prachi J. Natu, Shachi J. Natu, Dr. T. K. Sarode, Dr. H. B. Kekre
10.5120/916-1294

Prachi J. Natu, Shachi J. Natu, Dr. T. K. Sarode, Dr. H. B. Kekre . Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram. International Journal of Computer Applications. 5, 6 ( August 2010), 30-37. DOI=10.5120/916-1294

@article{ 10.5120/916-1294,
author = { Prachi J. Natu, Shachi J. Natu, Dr. T. K. Sarode, Dr. H. B. Kekre },
title = { Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 5 },
number = { 6 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume5/number6/916-1294/ },
doi = { 10.5120/916-1294 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:53:35.215336+05:30
%A Prachi J. Natu
%A Shachi J. Natu
%A Dr. T. K. Sarode
%A Dr. H. B. Kekre
%T Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram
%J International Journal of Computer Applications
%@ 0975-8887
%V 5
%N 6
%P 30-37
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper aims to provide different approaches to text dependent speaker identification using various transformation techniques such as DCT, Walsh and Haar transform along with use of spectrograms. Set of spectrograms obtained from speech samples is used as image database for the study undertaken. This image database is then subjected to various transforms. Using Euclidean distance as measure of similarity, most appropriate speaker match is obtained which is declared to be identified speaker. Each transform is applied to spectrograms in two different ways: on full image and on Row Mean of an image. In both the ways, effect of different number of coefficients of transformed image is observed. Further, comparison of all three transformation techniques on spectrograms in both the ways shows that numbers of mathematical computations required for Walsh transform is much lesser than number of mathematical computations required in case of DCT on spectrograms. Whereas, use of Haar transform on spectrograms drastically reduces the number of mathematical computation with almost equal identification rate. Transformation techniques on Row Mean give better identification rate than transformation technique on full image.

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Index Terms

Computer Science
Information Sciences

Keywords

Speaker identification Speaker Recognition Spectrograms DCT WALSH HAAR Row Mean