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Reseach Article

Real Time Speaker Recognition System using MFCC and Vector Quantization Technique

by Roma Bharti, Priyanka Bansal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 1
Year of Publication: 2015
Authors: Roma Bharti, Priyanka Bansal
10.5120/20520-2361

Roma Bharti, Priyanka Bansal . Real Time Speaker Recognition System using MFCC and Vector Quantization Technique. International Journal of Computer Applications. 117, 1 ( May 2015), 25-31. DOI=10.5120/20520-2361

@article{ 10.5120/20520-2361,
author = { Roma Bharti, Priyanka Bansal },
title = { Real Time Speaker Recognition System using MFCC and Vector Quantization Technique },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 1 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number1/20520-2361/ },
doi = { 10.5120/20520-2361 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:58:09.880045+05:30
%A Roma Bharti
%A Priyanka Bansal
%T Real Time Speaker Recognition System using MFCC and Vector Quantization Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 1
%P 25-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper represents a very strong mathematical algorithm for Automatic Speaker Recognition (ASR) system using MFCC and vector quantization technique in the digital world. MFCC and vector quantization techniques are the most preferable and promising these days so as to support a technological aspect and motivation of the significant progress in the area of voice recognition. Our goal is to develop a real-time speaker recognition system that has been trained for a particular speaker and verifies the speaker. ASR is a type of biometric that uses an individual's voice for recognition processes. Speaker-vocal discriminative parameters exist in speech signals and due to dissimilar resonances of different speakers speaker recognition system verifies the speaker. These different characteristics can be accomplished by extracting features in vector form like Mel-Frequency Cepstral Coefficient (MFCCs) from the audio signal. The Vector Quantization (VQ) technique maps vectors from a large vector space to a limited number of regions in the same multidimensional space. LBG (Linde, Buzo and Gray) algorithm is mostly used and preferred for clustering a set of L acoustic vectors into a set of M codebook vectors in speaker recognition.

References
  1. Rishiraj Mukherjee, Tanmoy Islam, and Ravi Sankar "text dependent speaker recognition using shifted mfcc" IEEE, 2013,.
  2. Hemlata Eknath Kamale, Dr. R. S. Kawitkar "Vector Quantization Approach for Speaker Recognition" International Journal of Computer Technology and Electronics Engineering (IJCTEE), Volume 3, , March-April 2013.
  3. Anjali Jain, O. P. Sharma "A Vector Quantization Approach for Voice Recognition Using Mel Frequency Cepstral Coeicient (MFCC): A Review" nternational Journal of electronics & communication technology, April - June 2013.
  4. Priyanka Mishra, Suyash Agrawal " Recognition of Speaker Using Mel Frequency Cepstral Coefficient & Vector Quantization" International Journal of Science, Engineering and Technology Research (IJSETR) ,December 2012
  5. A. Srinivasan , MAY 2012, "Speaker Identification and Verification using Vector Quantization and Mel Frequency Cepstral Coefficients" Research Journal of Applied Sciences, Engineering and Technology 4(1): 33-40, 2012
  6. Dipmoy Gupta, Radha Mounima C. Navya Manjunath, Manoj PB "Isolated Word Speech Recognition Using Vector Quantization (VQ)" International Journal of Advanced Research in Computer Science and Software Engineering , May 2012.
  7. Nitisha, Anshu Bansal "Speaker Recognition Using MFCC Front End Analysis and VQ Modeling Technique for Hindi Words using MATLAB" International Journal of Computer Applications (0975 8887) Volume 45 No. 24, May 2012.
  8. Prof. Ch. Srinivasa Kumar, Dr. P. Mallikarjuna Rao "Design Of An Automatic Speaker Recognition System Using MFCC, Vector Quantization And LBG Algorithm" international journal of computer science and Engineering (IJSCE); Aug 2011
  9. HarisBC, GPradhan, AMisra, SShukla, RSinha and SRMP rasanna" Multi-Variability Speech Database for Robust SpeakerRecognition" IEEE 2011.
  10. A. Stolcke, E. Shriberg, L. Ferrer, S. Kajarekar, K. Sonmez, G. Tur "speech recognition as feature extraction for speaker recognition" Speech Technology and Research Laboratory, SRI International, Menlo Park, CA, USA.
  11. Vibha Tiwari "MFCC and its applications in speaker recognition" International Journal on Emerging Technologies, 2010.
  12. Jeng-Shyang Pan, Zhe-Ming Lu, and Sheng-He Sun "An Efficient Encoding Algorithm for Vector Quantization Based on Subvector Technique", IEEE VOL. 12, NO. 3, March 2003.
  13. Linde, Y. , A. Buzo and R. Gray "An algorithm for vector quantizer design". IEEE Trans. Commun. , 2884-95,1980.
Index Terms

Computer Science
Information Sciences

Keywords

Mel frequency cepstrum coefficient (MFCC) speaker recognition speaker verification vector quantization (VQ).