A digital speech signal compression algorithm based on wavelet transform

Authors

  • G. F. Konakhovych National Aviation University
  • O. Y. Lavrynenko National Aviation University
  • V. V. Antonov National Aviation University
  • D. I. Bakhtiiarov National Aviation University

DOI:

https://doi.org/10.18372/1990-5548.48.11204

Keywords:

Digital speech signal, compression algorithm, speech coding, wavelet transform, entropy arithmetic coding, compression ratio, bit rate, correlation coefficient

Abstract

It is proposed to use developed digital speech signal compression algorithm based on wavelettransform using entropy arithmetic coding, which allows to achieve optimum results in the improvementof data compression while maintaining the intelligibility of speech signals. Substantiated and experimentallyproved the feasibility of using the speech compression algorithm. It is implemented the estimation ofcompression data ratio and bit rate depending on the parameters of the correlation coefficient, the signal/ noise ratio, peak signal / noise ratio and root-mean square error, which is the main criterion of performanceof speech quality. The results of experimental studies suggest the feasibility of further practicalapplication of the proposed digital speech signal compression algorithm based on wavelet transform intodifferent models of vocoding devices

Author Biographies

G. F. Konakhovych, National Aviation University

Doctor of Engineering. Professor. Institute of Air Navigation

O. Y. Lavrynenko, National Aviation University

Graduate Student. Institute of Air Navigation

V. V. Antonov, National Aviation University

Ph.D. Institute of Air Navigation

D. I. Bakhtiiarov, National Aviation University

Graduate Student. Institute of Air Navigation

References

I. Daubechies, Ten lectures on wavelets, CBMS-NSF conference series in applied mathematics, SIAM, 1992.

G. F. Konahovich, D. I. Bakhtiyarov, O. Y. Lavrynenko, “Computer modeling of drone protected control channel,” Science-Based Technologies, vol. 28, no. 4, pp. 283–290, 2015.

S. A. Mallat, “Theory for multiresolution signal decomposition: the wavelet representation,” IEEE Pattern Anal. and Machine Intell., vol. 11, no. 7, pp. 674–693, 1989.

M. J. Shensa, “The discrete wavelet transform: wedding the a trous and Mallat Algorithms,” IEEE Trans. on Signal Processing, vol. 40, no. 10, pp. 2464–2482, 1992.

G. F. Konahovich, O. I. Davletyants, O. Y. Lavrynenko, and D. I. Bakhtiyarov, “The comparative analysis the Fourier transform, cosine transform and wavelet transform as a spectral analysis of the digital speech signals,” Science-Based Technologies, vol. 27, no. 3, pp. 210–220, 2015.

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Issue

Vol. 2 No. 48 (2016)

Section

THEORY AND METHODS OF SIGNAL PROCESSING

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