Research Article Open Access

Speaker Recognition Using Spectral Cross-correlation: A Fast Algorithm

Zoubir Hamici1
  • 1 Amman University, Jordan

Abstract

This study presents an original algorithm for computing the cross-correlation function applied for speech recognition A spectral correlation estimation algorithm based on the comparing the magnitude spectrum of the two signals is presented. The number of samples is reduced by a factor of two, after eliminating the image spectrum. A moving average filter is used to smooth the magnitude spectrum and a re-sampling is performed in the frequency domain, which reduces the spectrum size, by a factor of 8. The algorithm shows good results in recognizing the voice of a specific person, hence its application in speaker identification.

Journal of Computer Science
Volume 1 No. 2, 2005, 84-88

DOI: https://doi.org/10.3844/jcssp.2005.84.88

Published On: 19 October 2005

How to Cite: Hamici, Z. (2005). Speaker Recognition Using Spectral Cross-correlation: A Fast Algorithm. Journal of Computer Science, 1(2), 84-88. https://doi.org/10.3844/jcssp.2005.84.88

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Keywords

  • Speaker recognition
  • spectral cross-correlation
  • fast algorithm