Design of Optimized Wavelet Packet Algorithm to Improve Perception of Sensorineural Hearing Impaired
- 1 SPPU Pune, Matoshri College of Engineering and Research, Nashik, India
- 2 Government College of Engineering and Research, Avasari, India
Abstract
A novel optimized wavelet packet algorithm is proposed to improve the perception of sensorineural hearing-impaired people. In this work, we have developed optimized wavelet packet along with, biorthogonal wavelet basis functions using MATLAB Code. Here, we have created eight bands based on auditory filters of quasi octave bandwidth. Evaluation was carried out by conducting listening tests on seven subjects with bilateral mild to severe sensorineural hearing loss. The speech material used for the listening test consisted of a set of fifteen nonsense syllables in VCV context. The test results show that the proposed algorithm improves the recognition score, speech quality and transmission of overall feature specifically over the unprocessed signal. The response time also reduces significantly.
- Moore, B.C.J. (1997) An Introduction to Psychology of Hearing. 4th Edition, Academic, London.
- Kulkarni, P.N. and Pandey, P.C. (2008) Optimizing the Comb Filters for Spectral Splitting of Speech to Reduce the Effect of Spectral Masking. IEEE-International Conference on Signal Processing, Communications and Networking, Madras Institute of Technology, Anna University, Chennai, 4-6 January 2008, 69-73. http://dx.doi.org/10.1109/icscn.2008.4447163
- Chaudhari, D.S. and Pandey, P.C (1998) Dichotic Presentation of Speech Signal with Critical Band Filtering for Improving Speech Perception. Proc. IEEE Int. Conf. Acoust., Speech and Signal Processing (ICASSP’98), Seattle, Washington, AE 3.1.
- Daubechies, I. (1992) Ten Lectures on Wavelets. Vol. 61. Society for Industrial and Applied Mathematics, Philadelphia.
- Nogueira, W., Giese, A., Edler, B. and Buchner, A. (2006) Wavelet Packet Filterbank for Speech Processing Strategies in Cochlear Implants. Proceedings of IEEE International Conference on Acoustic Speech, Signal Processing (ICASSP’06), 5, 14-19.
- Yao, J. and Zhang, Y. (2002) The Application of Bionic Wavelet Transform to Speech Signal Processing in Cochlear Implants using Neural Network Simulations. IEEE Transactions on Biomedical Engineering, 49, 1299-1309. http://dx.doi.org/10.1109/TBME.2002.804590
- Karmarkal, A., Kumar, A. and Patney, R.K. (2007) Design of Optimal Wavelet Packet Trees Based on Auditory Perception Criterion. IEEE Signal Processing Letters, 14, 240-243.
- Kolte, M.T. and Chaudhari, D.S. (2010) Evaluation of Speech Processing Schemes to Improve Perception of Sensorinural Hearing Impaired. Current Science, 98, 613-615.
- Zwicker, E.W. (1961) Subdivision of Audible Frequency Rangeinto Critical Bands (Freqenzgruppen). Journal of the Acoustical Society of America, 33, 248. http://dx.doi.org/10.1121/1.1908630
- Chopade, J.J. and Futane, N.P. (2015) Wavelet Based Scheme to Improve Performance of Hearing under Noisy Environment. International Journal of Computer Applications, 130, 57-61.
- Baskent, D. (2006) Speech Recognition in Normal Hearing and Sensorineural Hearing Loss as a Function of the Number of Spectral Channels. Journal of the Acoustical Society of America, 120, 2908-2925. http://dx.doi.org/10.1121/1.2354017
- Loizou, P.C., Mani, A. and Dorman, M.F. (2003) Dichotic Speech Recognition in Noise Using Reduced Spectral Cues. Journal of the Acoustical Society of America, 114, 475-483. http://dx.doi.org/10.1121/1.1582861