Perception-based Personalization of Hearing Aids using Gaussian Processes and Active Learning

Jens Brehm Bagger Nielsen, Jakob Nielsen, Jan Larsen

AbstractPersonalization of multi-parameter hearing aids involves an initial fitting followed by a manual knowledge-based trial-and-error fine-tuning from ambiguous verbal user feedback. The result is an often sub-optimal HA setting whereby the full potential of modern hearing aids is not utilized. This article proposes an interactive hearing-aid personalization system that obtains an
optimal individual setting of the hearing aids from direct perceptual user feedback. Results obtained with ten hearing-impaired subjects show that ten to twenty pairwise user assessments between different settings—equivalent to 5-10 min.—is sufficient for personalization of up to four hearing-aid parameters. A setting obtained by the system was significantly preferred by the subject over the initial fitting, and the obtained setting could be reproduced with reasonable precision. The system may have potential for clinical usage to assist both the hearing-care professional and the user.
KeywordsHearing Aids, Personalization, Individualization, Gaussian Process (GP), Active Learning, Pairwise Comparisons
TypeJournal paper [With referee]
JournalIEEE Transactions on Audio, Speech, and Language Processing
Year2015    Month January    Vol. 23    No. 1    pp. 162-173
PublisherIEEE
ISBN / ISSN10.1109/TASLP.2014.2377581
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


Back  ::  IMM Publications