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ISSN: 1552-6607 (Online)
Research Article Open Access

Speaker Identification Using Discrete Wavelet Transform

Shanthini Pandiaraj1 and K. R. Shankar Kumar2
  • 1 Karunya University, India
  • 2 , India

Abstract

This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition.

Journal of Computer Science
Volume 11 No. 1, 2015, 53-56

DOI: https://doi.org/10.3844/jcssp.2015.53.56

Submitted On: 20 June 2013 Published On: 22 September 2014

How to Cite: Pandiaraj, S. & Kumar, K. R. S. (2015). Speaker Identification Using Discrete Wavelet Transform. Journal of Computer Science, 11(1), 53-56. https://doi.org/10.3844/jcssp.2015.53.56

Open AccessCopyright: © 2015 Shanthini Pandiaraj and K. R. Shankar Kumar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Speaker Identification
  • Discrete Wavelets
  • Gaussian Mixture Model