Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

Speaker Recognition using Support Vector Machine

Print
PDF
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 87 - Number 2
Year of Publication: 2014
Authors:
Geeta Nijhawan
M. K. Soni
10.5120/15178-3379

Geeta Nijhawan and M K Soni. Article: Speaker Recognition using Support Vector Machine. International Journal of Computer Applications 87(2):7-10, February 2014. Full text available. BibTeX

@article{key:article,
	author = {Geeta Nijhawan and M. K. Soni},
	title = {Article: Speaker Recognition using Support Vector Machine},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {87},
	number = {2},
	pages = {7-10},
	month = {February},
	note = {Full text available}
}

Abstract

Speaker recognition is the process of recognizing the speaker based on characteristics such as pitch ,tone in the speech wave. Background noise influences the overall efficiency of speaker recognition system and is still considered as one of the most challenging issue in Speaker Recognition System (SRS). In this paper mel-frequency cepstral coefficients (MFCC) feature is used along with Vector Quantisation(VQ)-LBG [Linde, Buzo and Gray, 1980] algorithm for designing SRS. MFCC feature is extracted from the input speech and then vector quantization of the extracted MFCC features is done using VQLBG algorithm. It reduces the dimensionality of the input vector . These MFCCs are used as the speaker features for matching via Support Vector Machine (SVM) method. The experimental results show that the proposed text-dependent speaker identification system gives an accuracy rate of 95. 0%.

References

  • Ch. Srinivasa Kumar, Dr. P. Mallikarjuna Rao, 2011, "Design of an Automatic Speaker Recognition System using MFCC, Vector Quantization and LBG Algorithm'', International Journal on Computer Science and Engineering,Vol. 3 No. 8 ,pp:2942-2954.
  • Amruta Anantrao Malode,Shashikant Sahare,2012 , "Advanced Speaker Recognition", International Journal of Advances in Engineering & Technology ,Vol. 4, Issue 1, pp. 443-455.
  • A. Srinivasan, "Speaker Identification and verification using Vector Quantization and Mel frequency Cepstral Coefficients",Research Journal of Applied Sciences,Engineering and Technology 4(I):33-40,2012.
  • Vibha Tiwari, "MFCC and its applications in speaker recognition",International Journal on Emerging Technologies1(I):19-22(2010)
  • 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
  • Fu Zhonghua; Zhao Rongchun; "An overview of modeling technology of speaker recognition", IEEE Proceedings of the International Conference on Neural Networks and Signal Processing Volume 2, Page(s):887 – 891, Dec. 2003.
  • 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.
  • John G. Proakis and Dimitris G. Manolakis, "Digital Signal Processing", New Delhi: Prentice Hall of India. 2002.
  • Rudra Pratap. Getting Started with MATLAB 7. New Delhi: Oxford University Press, 2006
  • D. A. Reynolds, "Experimental evaluation of features for robust speaker identification," IEEE Trans. Speech Audio Process. , vol. 2(4), pp. 639-43, Oct. 1994.
  • L. Rabiner, and B. H. Juang"Fundamentals of Speech Recognition", Singapore: Pearson Education, 1993.
  • B. Yegnanarayana, K. Sharat Reddy, and S. P. Kishore, "Source and system features for speaker recognition using AANN models," in proc. Int. Conf. Acoust. , Speech, Signal Process. , Utah, USA, Apr. 2001.
  • C. S. Gupta, "Significance of source features for speaker recognition," Master's Thesis, Indian Institute of Technology Madras, Dept. of Computer Science and Engg. , Chennai, India, 2003.
  • Shi-Huang Chen and Yu-Ren Luo, Speaker Verification Using MFCC and Support Vector Machine, Proceedings of the International MultiConference of Engineers and Computer Scientists 2009 Vol I,IMECS 2009, March 18 - 20, 2009, Hong Kong
  • S. M. Kamruzzaman, A. N. M. Rezaul Karim, Md. Saiful Islam and Md. Emdadul Haque, Speaker Identification using MFCC-Domain Support Vector Machine.