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Speaker Recognition System using Gaussian Mixture Model

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Authors:
Athira Aroon, S.B. Dhonde
10.5120/ijca2015907193

Athira Aroon and S B Dhonde. Article: Speaker Recognition System using Gaussian Mixture Model. International Journal of Computer Applications 130(14):38-40, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Athira Aroon and S.B. Dhonde},
	title = {Article: Speaker Recognition System using Gaussian Mixture Model},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {130},
	number = {14},
	pages = {38-40},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

In this paper,features for text-independent speaker recognition has been evaluated. Speaker identification from a set of templates and analyzing speaker recognition rate by extracting several key features like Mel Frequency Cepstral Coefficients [MFCC] from the speech signals of those persons by using the process of feature extraction using MATLAB2013 .These features are effectively captured using feature matching technique like Gaussian Mixture Model [GMM] , with varying mixture components of mixture model and the analyzing its effect on recognition rate . Improve the speaker recognition rate by varying the input parameters of the classifier. The experiments are evaluated on TIMIT Database effectively for a speech signal sampled at 16kHz.

References

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Keywords

Gaussian Mixture Model [GMM] , Mel Frequency Cepstral Coefficients [MFCC], Speaker Recognition rate.