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http://dx.doi.org/10.9718/JBER.2007.28.2.271

Performance Evaluation of Cochlear Implants Speech Processing Strategy Using Neural Spike Train Decoding  

Kim, Doo-Hee (Department of Biomedical Engineering, College of Health Science, Yonsei University)
Kim, Jin-Ho (Department of Biomedical Engineering, College of Health Science, Yonsei University)
Kim, Kyung-Hwan (Department of Biomedical Engineering, College of Health Science, Yonsei University)
Publication Information
Journal of Biomedical Engineering Research / v.28, no.2, 2007 , pp. 271-279 More about this Journal
Abstract
We suggest a novel method for the evaluation of cochlear implant (CI) speech processing strategy based on neural spike train decoding. From formant trajectories of input speech and auditory nerve responses responding to the electrical pulse trains generated from a specific CI speech processing strategy, optimal linear decoding filter was obtained, and used to estimate formant trajectory of incoming speech. Performance of a specific strategy is evaluated by comparing true and estimated formant trajectories. We compared a newly-developed strategy rooted from a closer mimicking of auditory periphery using nonlinear time-varying filter, with a conventional linear-filter-based strategy. It was shown that the formant trajectories could be estimated more exactly in the case of the nonlinear time-varying strategy. The superiority was more prominent when background noise level is high, and the spectral characteristic of the background noise was close to that of speech signals. This confirms the superiority observed from other evaluation methods, such as acoustic simulation and spectral analysis.
Keywords
cochlear implants; speech processing strategy; neural spike train decoding;
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1 A. Goodsall, N. Condoleon, and R. Cummins, 'Replacing hearing aids,' Analyst Report, Cochlear Ltd., 20 Jun. 2003
2 M. F. Bear, B. W. Connors, and M.A. Paradiso, Neuroscience:Exploring the brain, 2nd Ed., Lippincott Williams & Wilkins, 2004, pp.357-384
3 K. H. Kim, S. S. Kim, and S. J. Kim, 'Improvement of spike train decoder under spike detection and classification errors using support vector machine,' Med. Biol. Eng. Comput., vol. 44, no. 1-2, pp.124-30, 2006   DOI
4 A. T. Neel, 'Formant detail needed for vowel identification,' J. Acoust. Soc. Am., vol. 5, pp.125-131, 2004
5 G. E. Peterson, H. L. Barney, 'Control methods used in study of the vowels,' J. Acoust. Soc. Am., vol. 24, pp.175-184, 1952   DOI
6 D. K. Warland, P. Reinagel, and M. Meister, 'Decoding visual information from a population of retinal ganglion cells,' J. Neurophysiol., vol. 78, pp.2336-50, 1997   DOI   PUBMED
7 P. C. Loizou, 'Introduction to cochlear implants,' Tutorial article on cochlear implants that appeared in the IEEE Signal Processing Magazine, Sept. 1998., pp. 101-130
8 B. S. Wilson, C. C. Finley, D. T. Lawson, R. D. Wolford, and M. Zerbi, 'Design and evaluation of a continuous interleaved sampling (CIS) processing strategy for multichannel cochlear implants,' J. Rehabil. Res. Dev., vol. 30, no.1, pp.110-116, 1993   PUBMED
9 L. M. Litvak, B. Delgutte, and D. K. Eddington, 'Improved temporal coding of sinusoids in electric stimulation of the auditory nerve using desynchronizing pulse trains,' J. Acoust. Soc. Am., vol. 14, pp.2079-2098, 2003
10 P. Mitchell, 'The prevalence, risk factors and impacts of hearing impairment in an older Australian Community: The Blue Mountains Hearing Study,' XXVI International Congress of Audiology, Melbourne, Australia, 2002
11 J. T. Rubinstein, 'How cochlear implants encode speech,' Curr. Opin. Otolaryngol. Head Neck Surg., vol. 12, no. 5, pp.444-448, 2004   DOI   PUBMED   ScienceOn
12 J. H. Kim, D. H. Kim, and K. H. Kim, 'A speech processing strategy for auditory prosthesis based on nonlinear filterbank model of biological cochlear,' World congress on Medical Physics and Biomedical Engineering, Seoul, Korea, 2006
13 E. N. Brown, R. E. Kass, and P. P. Mitra, 'Multiple neural spike train data analysis: state-of-the-art and future challenges,' Nature neuroscience, vol. 7, no. 5, pp.456-461, 2004   DOI   ScienceOn
14 L. Deng, C. D. Geisler, 'A composite auditory model for processing speech sounds,' J. Acoust. Soc. Am., vol. 82, pp.2001 - 2012, 1987   DOI
15 L. M. Litvak, B. Delgutte, and D. K. Eddington, 'Auditory nerve fiber responses to electric stimulation: modulated and unmodulated pulse trains,' J. Acoust. Soc. Am., vol. 110, pp.368 - 379, 2001   DOI
16 C. J. Sumner, L. P. O'Mard, E. A. Lopez-Poveda, and R. Meddis, 'A nolinear filter-bank model of the guinea-pig cochlear nerve:Rate responses,' J. Acoust. Soc. Am., vol. 113, pp.3264-3274, 2003   DOI   ScienceOn
17 D. B. Grayden, A. N. Burkitt, O. P.Kenny, J. C. Clarey, A. G. Paolini, and G. M. Clark, 'A cochlear implant speech processing strategy based on an auditory model,' in Proc. of 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, Dec. 2004, pp.491-296
18 J. C. Bruce, L. S. Irlicht, M. W. White, S. J. O'leary, S. Dynes, E. Javel, and G. M. Clark, 'A stochastic model of the eletrically stimulated auditory nerve: pulse-train response,' IEEE Trans. Biomed. Eng., vol. 46, no. 6, pp.630-637, 1999   DOI   ScienceOn
19 P. J. Blarney, R. C. Dowell, A. M Brown, G. M. Clark, and P. M. Seligman, 'Speech processing studies using an acoustic model of a multiple-channel cochlear implant,' J. Acoust. Soc. Am., vol. 76, pp.104-110, 1984   DOI   ScienceOn
20 J. T. Rubinstein, C. Turner, 'A novel acoustic simulation of cochlear implant hearing: effects of temporal fine structure,' in Proc. 1st International IEEE EMBS Conference, Neural Engineering, Mar. 2003, pp.142 - 145
21 B. S. Wilson, C. C Finley, D. T. Lawson, R. D. Wolford, D. K. Eddington, and W. M. Rabinowitz, 'Better speech recognition with cochlear implants,' Nature, vol. 352, pp.236 - 238, 1991   DOI   ScienceOn