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.

scholarly journals Effect of Noise Reduction Gain Errors on Simulated Cochlear Implant Speech Intelligibility

2019 ◽  
Vol 23 ◽  
pp. 233121651982593
Author(s):  
Abigail A. Kressner ◽  
Tobias May ◽  
Torsten Dau
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Speech Intelligibility ◽  
Low Frequency ◽  
Noise Estimation ◽  
Estimation Errors ◽  
Two Factors ◽  
Gain Errors ◽  
Speech Segments ◽  
Noise Reduction Algorithm

It has been suggested that the most important factor for obtaining high speech intelligibility in noise with cochlear implant (CI) recipients is to preserve the low-frequency amplitude modulations of speech across time and frequency by, for example, minimizing the amount of noise in the gaps between speech segments. In contrast, it has also been argued that the transient parts of the speech signal, such as speech onsets, provide the most important information for speech intelligibility. The present study investigated the relative impact of these two factors on the potential benefit of noise reduction for CI recipients by systematically introducing noise estimation errors within speech segments, speech gaps, and the transitions between them. The introduction of these noise estimation errors directly induces errors in the noise reduction gains within each of these regions. Speech intelligibility in both stationary and modulated noise was then measured using a CI simulation tested on normal-hearing listeners. The results suggest that minimizing noise in the speech gaps can improve intelligibility, at least in modulated noise. However, significantly larger improvements were obtained when both the noise in the gaps was minimized and the speech transients were preserved. These results imply that the ability to identify the boundaries between speech segments and speech gaps may be one of the most important factors for a noise reduction algorithm because knowing the boundaries makes it possible to minimize the noise in the gaps as well as enhance the low-frequency amplitude modulations of the speech.

scholarly journals A Two-Microphone Noise Reduction System for Cochlear Implant Users with Nearby Microphones—Part II: Performance Evaluation

2008 ◽  
Vol 2008 (1) ◽  
Author(s):  
Martin Kompis ◽  
Matthias Bertram ◽  
Pascal Senn ◽  
Joachim Müller ◽  
Marco Pelizzone ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction System

Comparative Performance of an Adaptive Directional Microphone System and a Multichannel Noise Reduction System

2006 ◽  
Vol 17 (04) ◽  
pp. 241-252 ◽  
Author(s):  
Kevin C.P. Yuen ◽  
Anna C.S. Kam ◽  
Polly S.H. Lau
Keyword(s):  
Noise Reduction ◽  
Speech Intelligibility ◽  
Hearing Aid ◽  
Recognition Performance ◽  
Comparative Performance ◽  
Sentence Recognition ◽  
Side Condition ◽  
Directional Microphone ◽  
Reduction System ◽  
Front Condition

The amplification outcomes of two hearing aid prescriptions, NAL-NL1 and Digital Perception Processing (DPP), of nine moderate to moderately severe hearing-impaired adults were compared in the same digital hearing instrument. NAL-NL1 aims at optimizing speech intelligibility while amplifying the speech signal to a normal overall loudness level (Dillon, 1999). DPP focuses on restoring loudness based on normal and impaired cochlear excitation models (Launer and Moore, 2003). In this comparison, DPP resulted in better sentence recognition performance than the NAL-NL1 algorithm in the signal-front/noise-side condition, and the two prescriptions gave similar performance in the signal-front/noise-front condition. Subjective evaluations by the participants using the Abbreviated Profile for Hearing Aid Benefit and sound quality comparisons did not give conclusive results between the two prescriptions.With each hearing aid prescription, the ability of the hearing aid circuitry to reduce the effects of noise was evaluated by a sentence-in-noise test in three conditions: (1) adaptive directional microphone (DAZ), (2) multichannel noise reduction system (FNC), and (3) a combination of FNC and DAZ (FNC + DAZ). In the signal-front/noise-side condition, DAZ and FNC + DAZ gave better performance than FNC in nearly all participants, whereas in the signal-front and noise-front evaluation, the conditions revealed no significant differences.

scholarly journals Transient noise reduction in cochlear implant users: a multi-band approach

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Karl-Heinz Dyballa ◽  
Phillipp Hehrmann ◽  
Volkmar Hamacher ◽  
Thomas Lenarz ◽  
Andreas Buechner
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Speech Intelligibility ◽  
Single Band ◽  
Processing Conditions ◽  
Multiple Frequency ◽  
Speech Processor ◽  
Speech Reception ◽  
Speech Reception Thresholds ◽  
Multi Band

A previously-tested transient noise reduction (TNR) algorithm for cochlear implant (CI) users was modified to detect and attenuate transients independently across multiple frequency-bands. Since speech and transient noise are often spectrally distinct, we hypothesized that benefits in speech intelligibility can be achieved over the earlier single- band design. Fifteen experienced CI users (49 to 72 years) were tested unilaterally using pre-processed stimuli delivered directly to a speech processor. Speech intelligibility in transient and soft stationary noise, subjective sound quality and the recognition of warning signals was investigated in three processing conditions: no TNR (TNRoff), single- band TNR (TNRsgl) and multi-band TNR (TNRmult). Notably, TNRmult improved speech reception thresholds (SRTs) in cafeteria noise and office noise by up to 3 dB over both TNRoff and TNRsgl, and yielded higher comfort and clarity ratings in cafeteria noise. Our results indicate that multi-band transient noise reduction may be advantageous compared to a single-band approach, and reveal a substantial overall potential for TNR to improve speech perception and listening comfort in CI users.

scholarly journals Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users

2021 ◽  
Vol 25 ◽  
pp. 233121652110059
Author(s):  
Ayham Zedan ◽  
Tim Jürgens ◽  
Ben Williges ◽  
Birger Kollmeier ◽  
Konstantin Wiebe ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Cochlear Implant ◽  
Noise Reduction ◽  
Speech Intelligibility ◽  
Hearing Aid ◽  
Minimum Variance ◽  
Contralateral Side ◽  
Head Movements ◽  
Minimum Variance Distortionless Response ◽  
Spatial Noise

This study investigated the speech intelligibility benefit of using two different spatial noise reduction algorithms in cochlear implant (CI) users who use a hearing aid (HA) on the contralateral side (bimodal CI users). The study controlled for head movements by using head-related impulse responses to simulate a realistic cafeteria scenario and controlled for HA and CI manufacturer differences by using the master hearing aid platform (MHA) to apply both hearing loss compensation and the noise reduction algorithms (beamformers). Ten bimodal CI users with moderate to severe hearing loss contralateral to their CI participated in the study, and data from nine listeners were included in the data analysis. The beamformers evaluated were the adaptive differential microphones (ADM) implemented independently on each side of the listener and the (binaurally implemented) minimum variance distortionless response (MVDR). For frontal speech and stationary noise from either left or right, an improvement (reduction) of the speech reception threshold of 5.4 dB and 5.5 dB was observed using the ADM, and 6.4 dB and 7.0 dB using the MVDR, respectively. As expected, no improvement was observed for either algorithm for colocated speech and noise. In a 20-talker babble noise scenario, the benefit observed was 3.5 dB for ADM and 7.5 dB for MVDR. The binaural MVDR algorithm outperformed the bilaterally applied monaural ADM. These results encourage the use of beamformer algorithms such as the ADM and MVDR by bimodal CI users in everyday life scenarios.

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