Digital Technologies
ISSN (Print): ISSN Pending ISSN (Online): ISSN Pending Website: http://www.sciepub.com/journal/dt Editor-in-chief: Piter Vorobienko
Open Access
Journal Browser
Go
Digital Technologies. 2015, 1(1), 1-3
DOI: 10.12691/dt-1-1-1
Open AccessArticle

Mel-Frequency Cepstral Coefficient (MFCC) - a Novel Method for Speaker Recognition

Asutosh das1, Manas Ranjan Jena2, and Kalyan Kumar Barik2

1Department. of ETC, SIET, Odisha

2Department. of ELTCE, VSSUT, BURLA, ODISHA

Pub. Date: August 12, 2014

Cite this paper:
Asutosh das, Manas Ranjan Jena and Kalyan Kumar Barik. Mel-Frequency Cepstral Coefficient (MFCC) - a Novel Method for Speaker Recognition. Digital Technologies. 2015; 1(1):1-3. doi: 10.12691/dt-1-1-1

Abstract

The purpose of this paper is to develop a speaker recognition system which can recognize speakers from their speech. The proposed system would be text dependent speaker recognition system means the user has to speak from a set of spoken words. Mel. Frequency cepstral coefficient is used in order to extract the features of speakers from their speech signal while VQ (LBG) is used for design of codebook from extracted features. In pattern matching we derive the VQ distortion between the utterances of unknown speaker to codebooks of known speaker. We have used Euclidean distance to compute VQ distortion. The system is implemented by using TIMIT database with 630 speakers having 10 speech files each. In our project we have chosen 30 speakers as well as 100 speakers from this database. The comparison of speaker recognition performance between 30 speakers and 100 speakers are also discussed.

Keywords:
ASV ASI LPC Mel DFT LPCC MFCC

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  L.R. Rabiner and R.W. Schafer, “Digital Processing of Speech Signals”, New Delhi: Prentice Hall of India. 2006.
 
[2]  J. P. Campbell, JR., “Speaker Recognition: A Tutorial”, Proceedings of the IEEE, vol. 85, no. 9, pp. 1437-1462, Sep 1997. J.M.Naik, speaker verification: A Tutorial”, IEEE Communication Magazine, pp.42-48, January 1990.
 
[3]  J.M.Naik,”speaker verification: A Tutorial” ,IEEE Communication Magazine, pp.42-48, January 1990.
 
[4]  Md. Rashidul Hasan, Mustafa Jamil, Md. Golam Rabbani Md. Saifur Rahman, “Speaker identification using mel frequency cepstral coefficients” 3rd International Conference on Electrical & Computer Engineering ICECE 2004, 28-30 December 2004, Dhaka, Bangladesh.
 
[5]  John G. Proakis and Dimitris G. Manolakis, “Digital Signal Processing”, New Delhi:Prentice Hall of India. 2002.
 
[6]  John G. Proakis and Dimitris G. Manolakis, “Digital Signal Processing”, New Delhi:Prentice Hall of India. 2002.
 
[7]  Jr. J.D. Hansen, J. & Proakis, J. “Discrete time processing of speech signal, 2nd edition, IEEE press, Newwork, 2000.
 
[8]  Y. Linde, A. Buzo & R. Gray, “An algorithm for vector quantizer design”, IEEE Transactions on Communications, Vol. 28, issue 1, Jan 1980 pp. 84-95.
 
[9]  Seddik, H.; Rahmouni, A.; Sayadi, M.; “Text independent speaker recognition using the Mel frequency cepstral coefficients and a neural network classifier” First International Symposium on Control, Communications and Signal Processing, Proceedings of IEEE 2004 Page(s): 631-634.