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Relative effects of WDRC and NR to HA output SNR (Yun et al., 2024)

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posted on 2024-06-14, 19:13 authored by Donghyeon Yun, Jennifer Lentz, Yi Shen

Purpose: Most modern hearing aids (HAs) employ wide dynamic range compression (WDRC) and noise reduction (NR) algorithms. It is known that the nonlinear effects of WDRC and NR cause changes to the output signal-to-noise ratio (SNR) of an HA. However, the relative contributions of WDRC and NR to the nonlinear effects are not fully understood. The current study investigated (a) whether WDRC or NR dominates the nonlinear effects measured at the output of a digital HA and (b) whether the electroacoustic effectiveness of NR depends on WDRC parameters while input SNR and background noise are systematically varied.

Method: Test stimuli were Connected Speech Test sentences in multitalker babble noise (2- or 20-talker), presented at input SNRs ranging from −10 to +10 dB. The HA was programmed using multiband WDRC set according to the National Acoustic Laboratories for Nonlinear HA fitting formula 2 prescriptive fits for four standard audiograms and two compression speeds. The NR algorithm of the HA was switched on or off in separate conditions. Nonlinear electroacoustic effects from the WDRC and NR algorithms were assessed by measuring the output SNR of the HA using a phase-inversion technique. To investigate whether there are other factors that may be important besides the output SNR, the Hearing Aid Speech Intelligibility Index and the Hearing Aid Speech Quality Index were applied to the recordings to generate inferences on aided speech intelligibility and perceived speech quality.

Results: Results showed that WDRC dominated the net nonlinear effect at low-input SNRs, and the net nonlinear effect of WDRC and NR was reduced at high-input SNRs. Results also showed that the effectiveness of NR depended on compression parameters. The effectiveness of NR was partially explained by the trend of Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores, potentially indicating that the Hearing Aid Speech Intelligibility Index and Hearing Aid Speech Quality Index scores may capture factors that cannot be captured by the output SNR metric.

Conclusions: Results suggest that the individual signal-processing stages in an HA should not be considered as independent. Electroacoustic evaluation of WDRC and NR algorithms in isolation is not sufficient to capture the combined nonlinear effect of the two algorithms.

Supplemental Material S1. A repeated-measures ANOVA, treating input SNR, the number of background talkers, compression speed, and audiogram as the independent variables, the individual 2-second time windows as the random effects factor, and output SNR as the dependent variable.

Supplemental Material S2. A repeated-measures ANOVA, treating compression speed, the number of background talkers, and audiogram as the independent variables, the individual 2-second time windows as the random effects factor, and output/input SNR slope as the dependent variable.

Supplemental Material S3. A repeated-measures ANOVA, treating input SNR, the number of background talkers, compression speed, and audiogram as the independent variables, the individual 2-second time windows as the random effects factor, and the difference in output SNR between the WDRC-only and WDRC+NR conditions as the dependent variable.

Yun, D., Lentz, J., & Shen, Y. (2024). The noise reduction algorithm may not compensate for the degradation in output signal-to-noise ratio caused by wide dynamic range compression. American Journal of Audiology. Advance online publication. https://doi.org/10.1044/2024_AJA-24-00011

Funding

This work was supported by National Institutes of Health Grant R01DC017988 (Principal Investigator: Y. Shen).

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