scholarly journals Multi-microphone adaptive noise reduction strategies for coordinated stimulation in bilateral cochlear implant devices

2010 ◽  
Vol 127 (5) ◽  
pp. 3136-3144 ◽  
Author(s):  
Kostas Kokkinakis ◽  
Philipos C. Loizou
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction Strategies ◽  
Bilateral Cochlear Implant ◽  
Adaptive Noise

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 Sparse grid-based adaptive noise reduction strategy for particle-in-cell schemes

2021 ◽  
pp. 100094
Author(s):  
Sriramkrishnan Muralikrishnan ◽  
Antoine J. Cerfon ◽  
Matthias Frey ◽  
Lee F. Ricketson ◽  
Andreas Adelmann
Keyword(s):  
Noise Reduction ◽  
Sparse Grid ◽  
Reduction Strategy ◽  
Particle In Cell ◽  
Adaptive Noise ◽  
Grid Based

scholarly journals An efficient Scheme to Remove Low Density Impulse Noise From A Digital Image

2016 ◽  
Vol 15 (12) ◽  
pp. 7284-7289
Author(s):  
Dr. Jihad N. Abdeljalil Al-Balqa
Keyword(s):  
Noise Reduction ◽  
Impulse Noise ◽  
Low Density ◽  
Salt And Pepper Noise ◽  
Reduction Scheme ◽  
Iir Filter ◽  
Noise Impulse ◽  
Efficient Scheme ◽  
Adaptive Noise ◽  
Salt And Pepper

An improved adaptive noise reduction scheme for images that are highly corrupted by Salt-and-Pepper noise(impulse noise), is proposed in this paper which efficiently removes the salt and pepper noise while preserving the details. The proposed scheme efficiently identifies and reduces salt and pepper noise. The algorithm utilizes an IIR filter with controlled parameters to get better image quality than the existing methods of noise removing. A comparative analysis between the proposed scheme and other techniques of noise reduction or removing is presented in order to show the advantages of the proposed scheme in removing the noisy pixels and producing a better PSNR.

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