Text Dependent Speaker Recognition system Using Vector Quantisation Technnique

Piyush Lotia*, Kamal K Mehta**, M. R. Khan***
* Research scholar, Electronics and Telecommunication, CSVTU BHILAI (C.G.), India.
**Associate Professor, ETC Shri Shankaracharya college of Engg. & Technology, Bhilai, India.
*** Principal, New Govt. Engineering College, Raipur (C.G.).
Periodicity:April - June'2010
DOI : https://doi.org/10.26634/jee.3.4.1190

Abstract

Automatic speaker recognition is a field of study attributed in identifying a person from a spoken phrase. It is widely used in biometric security system, phone banking and other similar applications. This paper presents a development of a Matlab based text dependent speaker recognition system. The model used to derive a mathematical representation of the speech signal. Mel Frequency Cepstrum Coefficient Feature extraction method is used to extract a speaker’s discriminative features from the mathematical representation of the speech signal. After that a feature matching method known as Vector Quantization is implemented using the LBG Algorithm. Feature matching is carried out in order to cluster the speech features into groups of specific sound classes. Finally analysis is carried out to identify parameter values that could be used to increase the accuracy of the system. In this paper we have studied the effect of recording environment on the accuracy of speaker identification.

Keywords

MFCC, VQ, Cepstrum, LBG Algorithm.

How to Cite this Article?

Piyush Lotia, Kamal Mehta and M. R. Khan (2010). Text Dependent Speaker Recognition System Using Vector Quantization Technique. i-manager’s Journal on Electrical Engineering. 3(4) Apr-Jun 2010, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 46-53. https://doi.org/10.26634/jee.3.4.1190

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