Active hearing protectors: Prospects for improving speech intelligibility while maintaining noise reduction and audibility of warning alarms

2005 ◽  
Vol 117 (4) ◽  
pp. 2480-2481
Author(s):  
Anthony J. Brammer ◽  
Donald R. Peterson ◽  
Martin G. Cherniack ◽  
Subhash Gullapalli
Keyword(s):  
Noise Reduction ◽  
Speech Intelligibility ◽  
Hearing Protectors

Improved Environment-Aware–Based Noise Reduction System for Cochlear Implant Users Based on Knowledge Transfer Approach (Preprint)

2020 ◽  
Author(s):  
Lieber Po-Hung Li ◽  
Ji-Yan Han ◽  
Wei-Zhong Zheng ◽  
Ren-Jie Huang ◽  
Ying-Hui Lai
Keyword(s):  
Knowledge Transfer ◽  
Cochlear Implant ◽  
Noise Reduction ◽  
Speech Intelligibility ◽  
Middle Layer ◽  
Successful Implementation ◽  
Perceptual Evaluation ◽  
Reduction System ◽  
Listening Tests ◽  
Implementation Costs

BACKGROUND The cochlear implant technology is a well-known approach to help deaf patients hear speech again. It can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction (NR), such as noise classification and deep denoising autoencoder (NC+DDAE), can benefit the intelligibility performance of patients with cochlear implants compared to classical noise reduction algorithms. OBJECTIVE Following the successful implementation of the NC+DDAE model in our previous study, this study aimed to (1) propose an advanced noise reduction system using knowledge transfer technology, called NC+DDAE_T, (2) examine the proposed NC+DDAE_T noise reduction system using objective evaluations and subjective listening tests, and (3) investigate which layer substitution of the knowledge transfer technology in the NC+DDAE_T noise reduction system provides the best outcome. METHODS The knowledge transfer technology was adopted to reduce the number of parameters of the NC+DDAE_T compared with the NC+DDAE. We investigated which layer should be substituted using short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) scores, as well as t-distributed stochastic neighbor embedding to visualize the features in each model layer. Moreover, we enrolled ten cochlear implant users for listening tests to evaluate the benefits of the newly developed NC+DDAE_T. RESULTS The experimental results showed that substituting the middle layer (ie, the second layer in this study) of the noise-independent DDAE (NI-DDAE) model achieved the best performance gain regarding STOI and PESQ scores. Therefore, the parameters of layer three in the NI-DDAE were chosen to be replaced, thereby establishing the NC+DDAE_T. Both objective and listening test results showed that the proposed NC+DDAE_T noise reduction system achieved similar performances compared with the previous NC+DDAE in several noisy test conditions. However, the proposed NC+DDAE_T only needs a quarter of the number of parameters compared to the NC+DDAE. CONCLUSIONS This study demonstrated that knowledge transfer technology can help to reduce the number of parameters in an NC+DDAE while keeping similar performance rates. This suggests that the proposed NC+DDAE_T model may reduce the implementation costs of this noise reduction system and provide more benefits for cochlear implant users.

Performance Improvement of Digital Hearing Aid Systems

2015 ◽  
Vol 1 ◽  
pp. 27
Author(s):  
Isiaka Ajewale Alimi
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Digital Signal Processor ◽  
Speech Intelligibility ◽  
Communication Systems ◽  
Hearing Aid ◽  
Spectral Subtraction ◽  
Residual Spectrum ◽  
Digital Hearing Aids ◽  
Digital Hearing Aid

Digital hearing aids addresses the issues of noise and speech intelligibility that is associated with the analogue types. One of the main functions of the digital signal processor (DSP) of digital hearing aid systems is noise reduction which can be achieved by speech enhancement algorithms which in turn improve system performance and flexibility. However, studies have shown that the quality of experience (QoE) with some of the current hearing aids is not up to expectation in a noisy environment due to interfering sound, background noise and reverberation. It is also suggested that noise reduction features of the DSP can be further improved accordingly. Recently, we proposed an adaptive spectral subtraction algorithm to enhance the performance of communication systems and address the issue of associated musical noise generated by the conventional spectral subtraction algorithm. The effectiveness of the algorithm has been confirmed by different objective and subjective evaluations. In this study, an adaptive spectral subtraction algorithm is implemented using the noise-estimation algorithm for highly non-stationary noisy environments instead of the voice activity detection (VAD) employed in our previous work due to its effectiveness. Also, signal to residual spectrum ratio (SR) is implemented in order to control the amplification distortion for speech intelligibility improvement. The results show that the proposed scheme gives comparatively better performance and can be easily employed in digital hearing aid system for improving speech quality and intelligibility.

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

2021 ◽  
Vol 25 ◽  
pp. 233121652110144
Author(s):  
Ilja Reinten ◽  
Inge De Ronde-Brons ◽  
Rolph Houben ◽  
Wouter Dreschler
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Speech Intelligibility ◽  
Response Times ◽  
Hearing Impaired ◽  
Listening Effort ◽  
Arithmetic Task ◽  
Test Retest Reliability ◽  
Influence Of Noise ◽  
Measured Response

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.

scholarly journals Improving speech intelligibility in active hearing protectors and communication headsets with subband processing

2013 ◽  
Author(s):  
Anthony J. Brammer ◽  
Gongqiang Yu ◽  
Eric R. Bernstein ◽  
Martin G. Cherniack ◽  
Donald R. Peterson
Keyword(s):  
Speech Intelligibility ◽  
Hearing Protectors ◽  
Subband Processing

Angle dependent effects for impulse noise reduction for hearing protectors.

2009 ◽  
Vol 126 (4) ◽  
pp. 2218
Author(s):  
William J. Murphy ◽  
Amir Khan ◽  
Edward L. Zechmann
Keyword(s):  
Noise Reduction ◽  
Impulse Noise ◽  
Hearing Protectors

Estimating the Performance of Sound Restoration Hearing Protectors by Using the Speech Intelligibility Index

2010 ◽  
Author(s):  
Amanda S. Azman ◽  
David S. Yantek
Keyword(s):  
Speech Intelligibility ◽  
Human Subject ◽  
Noise Sources ◽  
Test Fixture ◽  
Electronic Sound ◽  
Human Subject Testing ◽  
Hearing Protectors ◽  
Speech Intelligibility Index ◽  
Highly Correlated ◽  
The Impact

Despite advances in engineering noise controls and the use of administrative controls, miners are still dependent on hearing protection devices for prevention of noise-induced hearing loss. However, miners often raise concerns about the audibility of spoken communication when wearing conventional hearing protectors. Electronic technologies that selectively process and restore sounds from outside of hearing protectors have been suggested as a partial remedy to the audibility problem. To assess the potential benefits of this technology for miners, NIOSH tested the impact of nine electronic sound restoration hearing protectors on speech intelligibility in selected mining background noises. Because of the number of devices and potential settings of those devices, it was necessary to narrow the choices before conducting human subject testing. This was done by testing the nine devices on an acoustic test fixture (ATF) to acquire one-third-octave-band data, and then calculating the speech intelligibility index (SII) to determine estimates of performance across device, noise and setting. The estimates of speech intelligibility obtained with the SII are highly correlated with the intelligibility of speech under adverse listening conditions such as noise, reverberation, and filtering. The results of fixture based testing indicate that performance varies little between most devices, with few showing exceptionally good or poor estimated speech intelligibility. The most significant differences in estimated performance using the devices were between the different noise sources used, regardless of device or setting. The findings of this research were used to select the devices and settings for subsequent human subject based speech intelligibility testing. The human subject testing results largely concurred with the findings from the acoustic test fixture testing and calculation of speech intelligibility index. Specifically, variations in background noise led to the greatest differences in speech intelligibility.

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