Interactions Between Digital Noise Reduction and Reverberation: Acoustic and Behavioral Effects

Abstract

Background: Digital noise reduction (DNR) processing is used in hearing aids to enhance perception in noise by classifying and suppressing the noise acoustics. However, the efficacy of DNR processing is not known under reverberant conditions where the speech-in-noise acoustics are further degraded by reverberation.

Purpose: The purpose of this study was to investigate acoustic and perceptual effects of DNR processing across a range of reverberant conditions for individuals with hearing impairment.

Research design: This study used an experimental design to investigate the effects of varying reverberation on speech-in-noise processed with DNR.

Study sample: Twenty-six listeners with mild-to-moderate sensorineural hearing impairment participated in the study.

Data collection and analysis: Speech stimuli were combined with unmodulated broadband noise at several signal-to-noise ratios (SNRs). A range of reverberant conditions with realistic parameters were simulated, as well as an anechoic control condition without reverberation. Reverberant speech-in-noise signals were processed using a spectral subtraction DNR simulation. Signals were acoustically analyzed using a phase inversion technique to quantify improvement in SNR as a result of DNR processing. Sentence intelligibility and subjective ratings of listening effort, speech naturalness, and background noise comfort were examined with and without DNR processing across the conditions.

Results: Improvement in SNR was greatest in the anechoic control condition and decreased as the ratio of direct to reverberant energy decreased. There was no significant effect of DNR processing on speech intelligibility in the anechoic control condition, but there was a significant decrease in speech intelligibility with DNR processing in all of the reverberant conditions. Subjectively, listeners reported greater listening effort and lower speech naturalness with DNR processing in some of the reverberant conditions. Listeners reported higher background noise comfort with DNR processing only in the anechoic control condition.

Conclusions: Results suggest that reverberation affects DNR processing using a spectral subtraction algorithm in such a way that decreases the ability of DNR to reduce noise without distorting the speech acoustics. Overall, DNR processing may be most beneficial in environments with little reverberation and that the use of DNR processing in highly reverberant environments may actually produce adverse perceptual effects. Further research is warranted using commercial hearing aids in realistic reverberant environments.

Figure 1:

Mean air-conduction thresholds for participants. Error bars represent +/− 1 standard deviation.

Figure 2:

Change in SNR quantified using the Inversion method as a result of DNR processing across the different room conditions. The left and right panels show the acoustic effects at different input SNRs.

Figure 3:

Speech intelligibility scores in RAUs with and without DNR processing across the different room conditions. The left and right panels show intelligibility at different input SNRs. The error bars represent +/− 1 standard error.

Figure 4:

Speech intelligibility scores in RAUs collapsed across input SNR for each of the room conditions. The error bars represent +/− 1 standard error. * p<.05 after Bonferroni correction.

Figure 5:

Subjective listener ratings after the story listening task with and without DNR processing across the different room conditions. Panel A depicts subjective listening effort, Panel B depicts speech naturalness, and Panel C depicts background noise comfort. Y-axes of all the panels are oriented such that higher ratings reflect an improved state for the given scale. The error bars represent +/−1 standard error. * p<.05 after Bonferroni correction.

Figure 6:

Change in SNR quantified using the Inversion Method as a result of DNR processing across the different room conditions. Sentences were combined with either white noise (gray boxplot) or factory noise (white boxplot) at an input SNR of +5 dB.