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Reseach Article

Inverted Mel Feature Set based Text-Independent Speaker Identification using Finite Doubly Truncated Gaussian Mixture Model

by V. Sailaja, P. Sunitha, B. Vasantha Lakshmi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 2
Year of Publication: 2016
Authors: V. Sailaja, P. Sunitha, B. Vasantha Lakshmi
10.5120/ijca2016912369

V. Sailaja, P. Sunitha, B. Vasantha Lakshmi . Inverted Mel Feature Set based Text-Independent Speaker Identification using Finite Doubly Truncated Gaussian Mixture Model. International Journal of Computer Applications. 156, 2 ( Dec 2016), 14-16. DOI=10.5120/ijca2016912369

@article{ 10.5120/ijca2016912369,
author = { V. Sailaja, P. Sunitha, B. Vasantha Lakshmi },
title = { Inverted Mel Feature Set based Text-Independent Speaker Identification using Finite Doubly Truncated Gaussian Mixture Model },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 2 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 14-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number2/26680-2016912369/ },
doi = { 10.5120/ijca2016912369 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:01:30.033835+05:30
%A V. Sailaja
%A P. Sunitha
%A B. Vasantha Lakshmi
%T Inverted Mel Feature Set based Text-Independent Speaker Identification using Finite Doubly Truncated Gaussian Mixture Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 2
%P 14-16
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper provides an efficient approach for text-independent speaker identification using the Inverted Mel-frequency Cepstral Coefficients as feature set and Finite Doubly Truncated Gaussian Mixture as Model (FDTGMM). Over the years, Mel-Frequency Cepstral Coefficients (MFCC), modeled on the human auditory system, has been used as a standard acoustic feature set for speech related applications. Furthermore, it has been shown that the Inverted Mel-frequency Cepstral Coefficients (IMFCC) is also a useful feature set for Speaker identification, which contains information complementary to MFCC as, it covers high frequency region more closely. The performance of the developed model is studied through experimental evaluation with 45 speaker’s data base and identification accuracy.

References
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  5. Cohen A.C. Jr. “Estimating the Mean and Variance of Normal Populations from Singly and Doubly Truncated Samples”, Ann.Maths. Statist., 21, pp 557-569.1950.
  6. V Sailaja , K Srinivasa Rao & K V V S Reddy “Text Independent Speaker Identification Using Finite Doubly Truncated Gaussian Mixture Model”, International Journal of Information Technology and Knowledge Management July-December 2010, Volume 2, No. 2, pp. 475-480.
Index Terms

Computer Science
Information Sciences

Keywords

Speaker Identification IMFCC FDTGMM Identification accuracy.