Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
권호 표지

A New Hearing Aid Algorithm for Speech Discrimination using ICA and Multi-band Loudness Compensation

  • Lee Sangmin (Division of Bionics & Bioinformatics, Chonbuk National University) ;
  • Won Jong Ho (Dept. of Biomedical Engineering, Hanyang University) ;
  • Park Hyung Min (Dept. of Electrical and Computer Engineering and School of Computer Science, Carnegie Mellon University) ;
  • Hong Sung Hwa (Dept. of Otolaryngology-Head and Neck Surgery, Sungkyunkwan University School of medicine, Samsung Medical Center) ;
  • Kim In Young (Dept. of Biomedical Engineering, Hanyang University) ;
  • Kim Sun I. (Dept. of Biomedical Engineering, Hanyang University)
  • Published : 2005.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we proposed a new hearing aid algorithm to improve SNR(signal to noise ratio) of noisy speech signal and speech perception. The proposed hearing aid algorithm is a multi-band loudness compensation based independent component analysis (ICA). The proposed algorithm was compared with a conventional spectral subtraction algorithm on behind-the-ear type hearing aid. The proposed algorithm successfully separated a target speech signal from background noise and from a mixture of the speech signals. The algorithms were compared each other by means of SNR. The average improvement of SNR by ICA based algorithm was 16.64dB, whereas spectral subtraction algorithm was 8.67dB. From the clinical tests, we concluded that our proposed algorithm would help hearing aid user to hear clearly a target speech in noisy conditions.

Keywords

References

  1. M. Kompis, P. Feuz, G. Valentini, and M. Pelizzone, 'A combined fixed/ adaptive beam forming noise-reduction system for hearing aids', Engineering in Medicine and Biology Society, Proceedings of the 20th Annual International Conference of the IEEE, Vol. 6, pp.3136-3139, 1998
  2. A. Bell and T. Sejnowski, 'An Information-Maximization Approach to Blind Separation and Blind Deconvolution', Neural Computation, Vol. 7,pp.1129-1159, 1995 https://doi.org/10.1162/neco.1995.7.6.1129
  3. J. Anemuller and B. Kollmeier, 'Adaptive separation of acoustic source for anechoic conditions: A constrained frequency approach', Speech Communications, Vol. 39, pp.7995, 2003
  4. K. Torkkola, 'Blind separation of delayed sources based on information maximization', Acoustics, Speech, and Signal Processing, ICASSP '96, Conference Proceedings, 1996 IEEE International Conference, Vol. 6, pp.3509-3512, 1996
  5. W.A. Yost, Fundamentals of hearing: an introduction, Academic Press, pp. 193-203, 2000
  6. H. Dillon, 'Tutorial: Compression? Yes, but for low or high frequencies, for low or high intensities and with what response times', Ear and Hearing, pp. 287-307, 1996 https://doi.org/10.1097/00003446-199608000-00001
  7. Y. C. Park, 'High performance digital hearing aid processor with psychoacoustic loudness correction', ICCE '97, pp.100-101, 1997
  8. Noisex-92 database is from 'http://spib.rice.edu/spib/select_noise.html'