Effect of Noise Reduction on Cortical Speech-in-Noise Processing and Its Variance due to Individual Noise Tolerance

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Subong Kim ◽  
Yu-Hsiang Wu ◽  
Hari M. Bharadwaj ◽  
Inyong Choi
Keyword(s):  
Noise Reduction ◽  
Noise Tolerance ◽  
Speech In Noise

scholarly journals Multitasking with typical use of hearing aid noise reduction in older listeners

2018 ◽  
Author(s):  
Tim Schoof ◽  
Pamela Souza
Keyword(s):  
Speech Recognition ◽  
Noise Reduction ◽  
Hearing Aids ◽  
Recognition Task ◽  
Hearing Impaired ◽  
Improve Performance ◽  
Sentence Recognition ◽  
Monitoring Task ◽  
Speech In Noise ◽  
Dual Task Paradigm

Objective: Older hearing-impaired adults typically experience difficulties understanding speech in noise. Most hearing aids address this issue using digital noise reduction. While noise reduction does not necessarily improve speech recognition, it may reduce the resources required to process the speech signal. Those available resources may, in turn, aid the ability to perform another task while listening to speech (i.e., multitasking). This study examined to what extent changing the strength of digital noise reduction in hearing aids affects the ability to multitask. Design: Multitasking was measured using a dual-task paradigm, combining a speech recognition task and a visual monitoring task. The speech recognition task involved sentence recognition in the presence of six-talker babble at signal-to-noise ratios (SNRs) of 2 and 7 dB. Participants were fit with commercially-available hearing aids programmed under three noise reduction settings: off, mild, strong. Study sample: 18 hearing-impaired older adults. Results: There were no effects of noise reduction on the ability to multitask, or on the ability to recognize speech in noise. Conclusions: Adjustment of noise reduction settings in the clinic may not invariably improve performance for some tasks.

scholarly journals Personality captures dissociations of subjective versus objective noise tolerance

2021 ◽  
Author(s):  
Malte Wöstmann ◽  
Julia Erb ◽  
Jens Kreitewolf ◽  
Jonas Obleser
Keyword(s):  
Acoustic Noise ◽  
Health Hazard ◽  
Self Report ◽  
Statistical Control ◽  
Noise Tolerance ◽  
Noise Resistance ◽  
Total N ◽  
Speech In Noise ◽  
Two Samples ◽  
Big 5 Personality

Acoustic noise is pervasive in human environments. Some individuals are more tolerant to noise than others. We demonstrate the explanatory potential of Big-5 personality traits neuroticism (being emotionally unstable) and extraversion (being enthusiastic, outgoing) on subjective self-report and objective psycho-acoustic metrics of noise tolerance in two samples (total N = 1,103). Under statistical control for demographics and in agreement with pre-registered hypotheses, lower neuroticism and higher extraversion independently explained superior self-reported noise resistance, speech-in-noise comprehension, and acceptable background noise. Surprisingly, objective speech-in-noise comprehension instead increased with higher levels of neuroticism. In turn, the bias to subjectively overrate one’s own objective noise tolerance decreases with higher neuroticism but increases with higher extraversion. Of benefit to a solid framework of noise tolerance and tailored audiological treatments, these results show that personality explains inter-individual differences in coping with acoustic noise, which is a ubiquitous source of distraction and health hazard.

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

2020 ◽  
Vol 31 (01) ◽  
pp. 017-029
Author(s):  
Paul Reinhart ◽  
Pavel Zahorik ◽  
Pamela Souza
Keyword(s):  
Noise Reduction ◽  
Hearing Impairment ◽  
Hearing Aids ◽  
Background Noise ◽  
Speech Intelligibility ◽  
Spectral Subtraction ◽  
Listening Effort ◽  
Speech In Noise ◽  
Reverberant Environments ◽  
Speech Naturalness

AbstractDigital 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.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.This study used an experimental design to investigate the effects of varying reverberation on speech-in-noise processed with DNR.Twenty-six listeners with mild-to-moderate sensorineural hearing impairment participated in the study.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.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.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.

Fitting Noise Management Signal Processing Applying the American Academy of Audiology Pediatric Amplification Guideline: Verification Protocols

2016 ◽  
Vol 27 (03) ◽  
pp. 237-251 ◽  
Author(s):  
Susan Scollie ◽  
Charla Levy ◽  
Nazanin Pourmand ◽  
Parvaneh Abbasalipour ◽  
Marlene Bagatto ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Clinical Practice ◽  
Noise Reduction ◽  
Hearing Aids ◽  
Hearing Aid ◽  
Sound Quality ◽  
Speech In Noise ◽  
Verification Systems ◽  
Clinical Verification ◽  
Noise Management

Background: Although guidelines for fitting hearing aids for children are well developed and have strong basis in evidence, specific protocols for fitting and verifying some technologies are not always available. One such technology is noise management in children’s hearing aids. Children are frequently in high-level and/or noisy environments, and many options for noise management exist in modern hearing aids. Verification protocols are needed to define specific test signals and levels for use in clinical practice. Purpose: This work aims to (1) describe the variation in different brands of noise reduction processors in hearing aids and the verification of these processors and (2) determine whether these differences are perceived by 13 children who have hearing loss. Finally, we aimed to develop a verification protocol for use in pediatric clinical practice. Study Sample: A set of hearing aids was tested using both clinically available test systems and a reference system, so that the impacts of noise reduction signal processing in hearing aids could be characterized for speech in a variety of background noises. A second set of hearing aids was tested across a range of audiograms and across two clinical verification systems to characterize the variance in clinical verification measurements. Finally, a set of hearing aid recordings that varied by type of noise reduction was rated for sound quality by children with hearing loss. Results: Significant variation across makes and models of hearing aids was observed in both the speed of noise reduction activation and the magnitude of noise reduction. Reference measures indicate that noise-only testing may overestimate noise reduction magnitude compared to speech-in-noise testing. Variation across clinical test signals was also observed, indicating that some test signals may be more successful than others for characterization of hearing aid noise reduction. Children provided different sound quality ratings across hearing aids, and for one hearing aid rated the sound quality as higher with the noise reduction system activated. Conclusions: Implications for clinical verification systems may be that greater standardization and the use of speech-in-noise test signals may improve the quality and consistency of noise reduction verification cross clinics. A suggested clinical protocol for verification of noise management in children’s hearing aids is suggested.

Encoding of speech in noise in adults using hearing aids: effect of noise reduction algorithm

2019 ◽  
Vol 18 (2) ◽  
pp. 98-104
Author(s):  
Hiba Ahmed El-Assal ◽  
Amani Mohamed El-Gharib ◽  
Enaas Ahmad Kolkaila ◽  
Trandil Hassan Elmahallawy
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Reduction Algorithm ◽  
Speech In Noise ◽  
Noise Reduction Algorithm

Sound Quality Measures for Speech in Noise through a Commercial Hearing Aid Implementing "Digital Noise Reduction"

2005 ◽  
Vol 16 (05) ◽  
pp. 270-277 ◽  
Author(s):  
Todd A. Ricketts ◽  
Benjamin W.Y. Hornsby
Keyword(s):  
Speech Recognition ◽  
Noise Reduction ◽  
Hearing Aid ◽  
Quality Measures ◽  
Sound Quality ◽  
Strong Preference ◽  
Paired Comparisons ◽  
Speech In Noise ◽  
Speech Recognition In Noise

This brief report discusses the affect of digital noise reduction (DNR) processing on aided speech recognition and sound quality measures in 14 adults fitted with a commercial hearing aid. Measures of speech recognition and sound quality were obtained in two different speech-in-noise conditions (71 dBA speech, +6 dB SNR and 75 dBA speech, +1 dB SNR). The results revealed that the presence or absence of DNR processing did not impact speech recognition in noise (either positively or negatively). Paired comparisons of sound quality for the same speech in noise signals, however, revealed a strong preference for DNR processing. These data suggest that at least one implementation of DNR processing is capable of providing improved sound quality, for speech in noise, in the absence of improved speech recognition.

Subjective and Objective Evaluation of Noise Management Algorithms

2009 ◽  
Vol 20 (02) ◽  
pp. 089-098 ◽  
Author(s):  
Heidi Peeters ◽  
Francis Kuk ◽  
Chi-chuen Lau ◽  
Denise Keenan
Keyword(s):  
Noise Reduction ◽  
Speech Intelligibility ◽  
Objective Evaluation ◽  
Reduction Algorithm ◽  
Speech In Noise ◽  
Directional Microphone ◽  
Hearing In Noise ◽  
Listening Environments ◽  
Speech Intelligibility Index ◽  
Noise Reduction Algorithm

Purpose: To measure the subjective and objective improvement of speech intelligibility in noise offered by a commercial hearing aid that uses a fully adaptive directional microphone and a noise reduction algorithm that optimizes the Speech Intelligibility Index (SII). Research Design: Comparison of results on the Hearing in Noise Test (HINT) and the Acceptable Noise Level task (ANL). Study Sample: Eighteen participants with varying configurations of sensorineural hearing loss. Results: Both the directional microphone and the noise reduction algorithm improved the speech-in-noise performance of the participants. The benefits reported were higher for the directional microphone than the noise reduction algorithm. A moderate correlation was noted between the benefits measured on the HINT and the ANL for the directional microphone condition, the noise reduction condition, and the directional microphone plus noise reduction conditions. Conclusions: These results suggest that the directional microphone and the SII-based noise reduction algorithm may improve the SNR of the listening environments, and both the HINT and the ANL may be used to study their benefits.

Sign in / Sign up

Export Citation Format

Share Document