Perception-Based Personalization of Hearing Aids Using Gaussian Processes and Active Learning

Jens Brehm Nielsen, Jakob Nielsen, Jan Larsen

Research output: Contribution to journalJournal articleResearchpeer-review


Personalization 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 suboptimal 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.
Original languageEnglish
JournalIEEE/ACM Transactions on Audio, Speech, and Language Processing
Issue number1
Pages (from-to)162-173
Publication statusPublished - 2015


  • Communication, Networking and Broadcast Technologies
  • Computing and Processing
  • General Topics for Engineers
  • Signal Processing and Analysis
  • Active learning
  • Approximation methods
  • Gain
  • Gaussian process (GP)
  • Gaussian processes
  • hearing aids
  • individualization
  • pairwise comparisons
  • personalization
  • Signal processing algorithms
  • Speech
  • Speech processing

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