Acoustic simulation of cochlear implant hearing

Authors

  • Anja Chilian Fraunhofer Institute for Digital Media Technology IDMT, D-98693 Ilmenau, Germany; Institute of Biomedical Engineering and Informatics, Faculty of Computer Science and Automation, Ilmenau University of Technology, D-98693 Ilmenau, Germany
  • Elisabeth Braun Fraunhofer Institute for Digital Media Technology IDMT, D-98693 Ilmenau, Germany; Institute of Biomedical Engineering and Informatics, Faculty of Computer Science and Automation, Ilmenau University of Technology, D-98693 Ilmenau, Germany
  • Tamas Harczos Fraunhofer Institute for Digital Media Technology IDMT, D-98693 Ilmenau, Germany; Institute for Media Technology, Faculty of Electrical Engineering and Information Technology, Ilmenau University of Technology, D-98693 Ilmenau, Germany

Abstract

One aim in current cochlear implant (CI) research is to improve and opti- mize speech processing strategies. During the development of new strate- gies acoustic simulations of CI hearing have widely been used for evalua- tion. These models usually take audio signals as input and mimic the effects of CI signal processing. In the present paper a new algorithm of acoustic simulation is presented, which transforms stimulation patterns of any co- chlear implant directly into an audio signal. Therefore it is independent of the CI strategy used for generating the stimulation pattern. Technical aspects like current spread and physiological aspects including loudness perception and phase locking capabilities of the simulated CI listener can be config- ured. The presented algorithm was used to evaluate and compare two differ- ent CI speech processing strategies in terms of speech intelligibility and pitch discrimination. The results show that acoustic simulation can help es- timate the amount of useful information in a CI stimulation pattern and hence be a help in evaluating CI strategies.

References

Bingabr, M., Espinoza-Varas, B., and Loizou, P. C. (2008). “Simulating the effect of spread of excitation in cochlear implants“ Hearing Research, 241, 73-79.

Black, R. C., Clark, G. M., Tong, Y. C., and Patrick, J. F. (1983). “Current distribu- tions in cochlear stimulation” Ann. N.Y. Acad. Sci., 405, 137-145.

Dorman, M.F., Loizou, P.C., and Rainey, D. (1997) “Speech intelligibility as a func- tion of the number of channels of stimulation for signal processors using sine- wave and noise-band outputs“ J. Acoust. Soc. Am., 102, 2403-2411.

Fu, Q. J. and Shannon, R. V. (1998). “Simulating effects of amplitude nonlinearity on phoneme recognition by cochlear implant users and normal-hearing listen- ers“ J. Acoust. Soc. Am., 104, 2570-2577.

Greenwood, D. D. (1990). “A cochlear frequency-position function for several spe- cies - 29 years later“ J. Acoust. Soc. Am., 87, 2592-2605.

Kral, A., Hartmann, R., Mortazavi, D., and Klinke, R. (1998). “Spatial resolution of cochlear implants : The electrical field and excitation of auditory afferents” Hearing Research, 121, 11-28.

Shannon, R.V., Zeng, F.G., Kamath, V., Wygonski, J., and Ekelid, M. (1995). “Speech recognition with primarily temporal cues” Science, 270, 303-304.

de la Torre Vega, Á., Martí, M. B., de la Torre Vega, R., and Quevedo, M. S. (2004). “Cochlear implant simulation version 2.0 : Description and usage of the program“ University of Granada, Spain.

Additional Files

Published

2011-12-15

How to Cite

Chilian, A., Braun, E., & Harczos, T. (2011). Acoustic simulation of cochlear implant hearing. Proceedings of the International Symposium on Auditory and Audiological Research, 3, 425–432. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2011-49

Issue

Section

2011/4. Recent concepts in hearing-instrument processing and fitting