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Bulletin of the Polish Academy of Sciences Technical Sciences

The Journal of Polish Academy of Sciences

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Volume 62, Issue 3 (Sep 2014)

Issues

Biometric speech signal processing in a system with digital signal processor

T. Marciniak
  • Corresponding author
  • Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems, Poznan University of Technology, 24 Jana Pawła II St., 60-965 Poznań, Poland
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ R. Weychan
  • Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems, Poznan University of Technology, 24 Jana Pawła II St., 60-965 Poznań, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ A. Stankiewicz
  • Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems, Poznan University of Technology, 24 Jana Pawła II St., 60-965 Poznań, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ A. Dąbrowski
  • Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems, Poznan University of Technology, 24 Jana Pawła II St., 60-965 Poznań, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2014-09-09 | DOI: https://doi.org/10.2478/bpasts-2014-0064

Abstract

This paper presents an analysis of issues related to the fixed-point implementation of a speech signal applied to biometric purposes. For preparing the system for automatic speaker identification and for experimental tests we have used the Matlab computing environment and the development software for Texas Instruments digital signal processors, namely the Code Composer Studio (CCS). The tested speech signals have been processed with the TMS320C5515 processor. The paper examines limitations associated with operation of the realized embedded system, demonstrates advantages and disadvantages of the technique of automatic software conversion from Matlab to the CCS and shows the impact of the fixed-point representation on the speech identification effectiveness.

Keywords : biometry; speech processing; digital signal processor; Gaussian mixture models; vector quantization

References

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About the article

Published Online: 2014-09-09

Published in Print: 2014-09-01


Citation Information: Bulletin of the Polish Academy of Sciences Technical Sciences, ISSN (Online) 2300-1917, DOI: https://doi.org/10.2478/bpasts-2014-0064.

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© Bulletin of the Polish Academy of Sciences. Technical Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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