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FPGA Implementation of Hearing Aids using Stationary Wavelet-Packets for Denoising

by Nivin Ghamry
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 15
Year of Publication: 2013
Authors: Nivin Ghamry
10.5120/11921-8125

Nivin Ghamry . FPGA Implementation of Hearing Aids using Stationary Wavelet-Packets for Denoising. International Journal of Computer Applications. 69, 15 ( May 2013), 30-36. DOI=10.5120/11921-8125

@article{ 10.5120/11921-8125,
author = { Nivin Ghamry },
title = { FPGA Implementation of Hearing Aids using Stationary Wavelet-Packets for Denoising },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 15 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 30-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number15/11921-8125/ },
doi = { 10.5120/11921-8125 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:30:23.338950+05:30
%A Nivin Ghamry
%T FPGA Implementation of Hearing Aids using Stationary Wavelet-Packets for Denoising
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 15
%P 30-36
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech signals are often contaminated with acoustic noise, which is present in a variety of listening environments. This problem is of critical importance because background noise is particularly damaging to speech intelligibility for people with hearing loss and hearing aids users. A pre-processing step in modern digital hearing aids is denoising to estimate the signal in the band of interest from the available noisy signals without altering it. Advances in digital signal processing have allowed adding vital features to improve the performance of assistive listening devices like speech enhancement and noise reduction. Furthermore, the progress in field programmable gate arrays (FPGA) technology,especially for miniaturized system applications facilitated the implementation of small, portable and high performance devices. In this paper a signal processing core based on stationary wavelet packets is designed forspeech enhancement and denoising in hearing aids. The developed core is implemented on FPGA and interconnected with embedded microprocessors and related peripherals to form a complete system on a programmable chip. The embedded software processor is Micro Blaze soft core processor. The chip used is Diligent XUP II Virtex-II Pro system FPGA containing audio codec LM4550. The features of the proposed design are intelligibility, small area and low cost.

References
  1. B. C . J Moore, Basic auditory processes involved in the analysis of speech sounds, Philosophical. Transaction of the Royal Society 363 (2008), 947-963.
  2. D. L. Donoho, and I. M. Johnstone, Ideal spatial adaptation via wavelet shrinkage, Biometrika81 (1994), 425-455.
  3. G. P. Nason, B. W. Silverman, The stationary wavelet transform and some statistical applications, Lecture Notes in Statistics 103 (1995), 281-299.
  4. G. S. Mihov, R. M. Ivanov, Angel N. Popov, Denoising Speech Signals by Wavelet Transform, Journal of Rehabilitation Research and Development 38 (2001), 111–121.
  5. H. Levitt, Noise reduction in hearing aids: a review, Journal of Rehabilitation Research and Development 38(2001), 11–121.
  6. H. Levitt, A historical perspective on digital hearing aids: How digital technology has changed modern hearing aids, Trends in Amplification 11 (2007), 7-24.
  7. K. . Paliwal and A. Basu, A Speech enhancement method based on kalman filtering in Proceeding of IEEE International Conference on Acoustics, Speech, and signal processing (ICASSP'87) 12 (1987), 297 – 300.
  8. L. A. , Drake, J. C. Rutledge, and J. Cohen, Wavelet analysis in recruitment of loudness compensation, IEEE Transaction on Signal Processing, 41(1993), 3306 – 3312.
  9. M. A. Trenas, , J. C. Rutledge and N. A. Whitmal,, Wavelet-based noise reduction and compression for hearing aids, Proceedings of the first joint Engineering in Medicine and Biology conference (BMES/EMBS) 1 (1999), 670-673 .
  10. M. A. Trenas, , J. Ldpez and E. L Zapata, An architecture for wavelet-packet based speech enhancement for hearing aids, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2 (2000), II849 - II852.
  11. M. Lavielle, Detection of multiple changes in a sequence of dependent variables, Stochastic Processes and their Applications,Elsevier Science83 (1999) 79-102.
  12. M. S. Chavan, M. N. Chavan and M. S. Gaikwad, Studies on implementation of wavelet for denoising speech signal, International Journal of Computer Application 3 (2010), 1-7.
  13. N. Whitmal, Janet. Rutledge, J. Cohen, Denoising speech signals for digital hearing aids: A wavelet based approach, Wavelets and Multiscale AnalysisApplied and Numerical Harmonic Analysis (2011), 299-331.
  14. R. C. Nongpiur and D. J. Shpak, Impulse-noise suppression in speech using the stationary wavelet transform, Journal of the Acoustical Society of America133 (2013), 866-879.
  15. R. K Young, Wavelet theory and its applications, Kluwer Academic Publisher, USA, 1993.
  16. R. R. ; Coifman, M. V Wickerhauser, Signal processing and compression with wave packets, Numerical Algorithms Research Group, New Haven, CT Yale University, 1990.
  17. R. R. Coifman, M. V Wickerhauser, Entropy-based algorithms for best basis selection, IEEE Transaction on Information Theory, 38 (1992), 713-718.
  18. S. D. Apte and R. Shahu, Speech enhancement in hearing aids using conjugate symmetry of DFT and SNR-perception models, International Journal of Computer Application 1 (2010), 44-51.
  19. V. H. Kumar and P. S. Ramaiah, Computerized speech processing in hearing aids using FPGA architecture, Journal of Computer Science and technology (IJACSA) 2, (2011) 106-111.
  20. V. H. Kumar and P. S. Ramaiah, Digital speech processing design for FPGA architecture for auditory prostheses, J0urnal of Computer Science and engineering (JCSE) 6 (2011) 33-41.
  21. Y. Min, Designofportable hearing aid basedonFPGA,Proceedings of the4thIEEE International ConferenceofIndustrial, Electronics and applications(2009), ICIEA, 1895-1899.
  22. Y. Ephraim and H. V. Trees, A Signal subspace approach for speech enhancement, IEEE Transaction on Speech Audio Processing 3 (1995), 251-266.
  23. Y. Ephraim and D. Malah, Speech enhancement using a minimum mean –square error log-spectral amplitude estimator, IEEE Transaction Acoustics, Speech, Signal Processing ASSP-33(1985), 443-445.
  24. Y Hao, X Zhu, A new feature in speech recognition based on wavelet transform. Proceedings of IEEE 5th Inter Conf on Signal Processing (WCCC-ICSP 2000), 1526–1529.
  25. Z. De-xiang, G. Qing-wie and C. Jun-ningpages, Single channel speech enhancement by de-noising using stationary wavelet transform, Journal of Electronic Science and Technology of China 4 (2006), 39-42.
  26. http://www. xilinx. com
Index Terms

Computer Science
Information Sciences

Keywords

denoising hearing aids FPGA Micro Blaze LM4550 stationary wavelet transform wavelet packets

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