Subjective evaluation of single microphone noise reduction with different time constants

Effective hearing aid (HA) rehabilitation requires personalization of the HA fitting parameters, but in current clinical practice only the gain prescription is typically individualized. To optimize the fitting process, advanced HA settings such as noise reduction and microphone directionality can also be tailored to individual hearing deficits. In two earlier studies, an auditory test battery and a data-driven approach that allow classifying hearing-impaired listeners into four auditory profiles were developed. Because these profiles were found to be characterized by markedly different hearing abilities, it was hypothesized that more tailored HA fittings would lead to better outcomes for such listeners. Here, we explored potential interactions between the four auditory profiles and HA outcome as assessed with three different measures (speech recognition, overall quality, and noise annoyance) and six HA processing strategies with various noise reduction, directionality, and compression settings. Using virtual acoustics, a realistic speech-in-noise environment was simulated. The stimuli were generated using a HA simulator and presented to 49 habitual HA users who had previously been profiled. The four auditory profiles differed clearly in terms of their mean aided speech reception thresholds, thereby implying different needs in terms of signal-to-noise ratio improvement. However, no clear interactions with the tested HA processing strategies were found. Overall, these findings suggest that the auditory profiles can capture some of the individual differences in HA processing needs and that further research is required to identify suitable HA solutions for them.

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confidence: 99%

Investigating the Effects of Four Auditory Profiles on Speech Recognition, Overall Quality, and Noise Annoyance With Simulated Hearing-Aid Processing Strategies

Sanchez-Lopez

El-Haj-Ali

et al. 2020

“…A possible and promising explanation for the spread of preference is the individual trade-off between noise tolerance and distortion tolerance. Several researchers have used this trade-off theory to explain individual differences in preferences for NR settings (Brons, Houben, et al, 2014; Houben et al, 2013; Luts et al, 2010; Neher & Wagener, 2016; Reinten et al, 2019; Rohdenburg et al, 2005; Völker et al, 2018). Sugiyama et al (2022) assessed individual differences in tolerance for signal distortion and residual noise using a single-channel speech enhancement algorithm.…”

Section: Discussionmentioning

confidence: 99%

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

Houben,

Reinten,

Dreschler

et al. 2023

Self Cite

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.

“…This may explain why on average we found no effect of the MMSE algorithm. This trade-off is known to be a complicating factor in the interpretation of NR benefits, especially because of the large variability in individual preferences for NR settings ( Neher, 2014 ; Reinten et al., 2019 ). Moreover, Neher (2014) concluded that executive functions can contribute to the interindividual variability in NR preferences.…”

Section: Discussionmentioning

confidence: 99%

Measuring the Influence of Noise Reduction on Listening Effort in Hearing-Impaired Listeners Using Response Times to an Arithmetic Task in Noise

Reinten

Ronde-Brons

Houben³

et al. 2021

Self Cite

Single microphone noise reduction (NR) in hearing aids can provide a subjective benefit even when there is no objective improvement in speech intelligibility. A possible explanation lies in a reduction of listening effort. Previously, we showed that response times (a proxy for listening effort) to an auditory-only dual-task were reduced by NR in normal-hearing (NH) listeners. In this study, we investigate if the results from NH listeners extend to the hearing-impaired (HI), the target group for hearing aids. In addition, we assess the relevance of the outcome measure for studying and understanding listening effort. Twelve HI subjects were asked to sum two digits of a digit triplet in noise. We measured response times to this task, as well as subjective listening effort and speech intelligibility. Stimuli were presented at three signal-to-noise ratios (SNR; –5, 0, +5 dB) and in quiet. Stimuli were processed with ideal or nonideal NR, or unprocessed. The effect of NR on response times in HI listeners was significant only in conditions where speech intelligibility was also affected (–5 dB SNR). This is in contrast to the previous results with NH listeners. There was a significant effect of SNR on response times for HI listeners. The response time measure was reasonably correlated ( R142 = 0.54) to subjective listening effort and showed a sufficient test–retest reliability. This study thus presents an objective, valid, and reliable measure for evaluating an aspect of listening effort of HI listeners.