A theoretical comparison of information transmission in the peripheral auditory system: Normal and impaired frequency discrimination
A theoretical analysis of auditory signal processing and the distortions introduced by various types of hearing impairments can aid in the design and development of digital hearing aids. In this paper, we investigate the differences between normal and impaired auditory processing on a frequency discrimination task by analyzing the responses of a computational auditory model using signal detection theory. Hearing impairments that were simulated included a threshold shift, damage to the outer hair cells, and impaired neural synchrony. We implemented two detectors, one using all of the information in the signal, the other using only the number of neural firings, and used them to generate theoretical predictions of performance. Evaluation of performance differences between theoretical detectors and experimental data allows quantification of both the type of information present in the auditory system and the efficiency of its use. This method of analysis predicted both the trends observed in comparable experimental data and the relation between normal and impaired behavior. Finally, a very simple hearing aid was simulated and the gains in performance in the impaired cases were related to the physiological bases of the impairments. This demonstrates the utility of the proposed approach in the design of more complex hearing aids. © 2002 Elsevier Science B.V. All rights reserved.
Duke Scholars
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Related Subject Headings
- Speech-Language Pathology & Audiology
- 4704 Linguistics
- 4602 Artificial intelligence
- 4006 Communications engineering
- 2004 Linguistics
- 1702 Cognitive Sciences
- 0801 Artificial Intelligence and Image Processing
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Speech-Language Pathology & Audiology
- 4704 Linguistics
- 4602 Artificial intelligence
- 4006 Communications engineering
- 2004 Linguistics
- 1702 Cognitive Sciences
- 0801 Artificial Intelligence and Image Processing