Preferred Strength of Noise Reduction for Normally Hearing and Hearing-Impaired Listeners

Rolph Houben, Ilja Reinten, Wouter A. Dreschler, Roland Mathijssen, Tjeerd M. H. Dijkstra

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Preference for noise reduction (NR) strength differs between individuals. The purpose of this study was (1) to investigate whether hearing loss influences this preference, (2) to find the number of distinct settings required to classify participants in similar groups based on their preference for NR strength, and (3) to estimate the number of paired comparisons needed to predict to which preference group a participant belongs. A paired comparison paradigm was used in which participants listened to pairs of speech-in-noise stimuli processed by NR with 10 different strength settings. Participants indicated their preferred sound sample. The 30 participants were divided into three groups according to hearing status (normal hearing, mild hearing loss, and moderate hearing loss). The results showed that (1) participants with moderate hearing loss preferred stronger NR than participants with normal hearing; (2) cluster analysis based solely on the preference for NR strength showed that the data could be described well by dividing the participants into three preference clusters; (3) the appropriate cluster membership could be found with 15 paired comparisons. We conclude that on average, a higher hearing loss is related to a preference for stronger NR, at least for our NR algorithm and our participants. The results show that it might be possible to use a limited set of pre-set NR strengths that can be chosen clinically. For our NR one might use three settings: no NR, intermediate NR, and strong NR. Paired comparisons might be used to find the optimal one of the three settings.
Original languageEnglish
JournalTrends in Hearing
Volume27
DOIs
Publication statusPublished - 1 Jan 2023

Keywords

  • hearing aids
  • hearing loss
  • paired comparison study
  • subjective evaluation
  • user preference analysis

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