Exploration of a physiologically-inspired hearing aid algorithm using a computer model mimicking impaired hearing

Jürgens, T and Clark, N.R and Lecluyse, Wendy and Meddis, R (2016) Exploration of a physiologically-inspired hearing aid algorithm using a computer model mimicking impaired hearing. International Journal of Audiology, 55 (6). pp. 346-357. ISSN 1499-2027

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Objective: To use a computer model of impaired hearing to explore the effects of a physiologically-inspired hearing-aid algorithm on a range of psychoacoustic measures. Design: A computer model of a hypothetical impaired listener’s hearing was constructed by adjusting parameters of a computer model of normal hearing. Absolute thresholds, estimates of compression, and frequency selectivity (summarized to a hearing profile) were assessed using this model with and without pre-processing the stimuli by a hearing-aid algorithm. The influence of different settings of the algorithm on the impaired profile was investigated. To validate the model predictions, the effect of the algorithm on hearing profiles of human impaired listeners was measured. Study sample: A computer model simulating impaired hearing (total absence of basilar membrane compression) was used, and three hearing-impaired listeners participated. Results: The hearing profiles of the model and the listeners showed substantial changes when the test stimuli were pre-processed by the hearing-aid algorithm. These changes consisted of lower absolute thresholds, steeper temporal masking curves, and sharper psychophysical tuning curves. Conclusion: The hearing-aid algorithm affected the impaired hearing profile of the model to approximate a normal hearing profile. Qualitatively similar results were found with the impaired listeners’ hearing profiles.

Item Type: Article
Uncontrolled Keywords: Auditory model, algorithm evaluation, normal and impaired hearing, psychoacoustics
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Arts, Business & Applied Social Science > Department of Applied Social Sciences
Depositing User: David Upson-Dale
Date Deposited: 28 Nov 2017 10:55
Last Modified: 28 Nov 2017 10:55
URI: http://oars.uos.ac.uk/id/eprint/292

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