Improving word recognition in noise among hearing-impaired subjects with a single-channel cochlear noise-reduction algorithm

2012 ◽  
Vol 132 (3) ◽  
pp. 1718-1731 ◽  
Author(s):  
Nir Fink ◽  
Miriam Furst ◽  
Chava Muchnik
Keyword(s):  
Word Recognition ◽  
Noise Reduction ◽  
Single Channel ◽  
Hearing Impaired ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

scholarly journals Noise reduction in hearing aids using spectral subtraction techniques

2021 ◽  
Author(s):  
Fatos Myftari
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Speech Intelligibility ◽  
Single Channel ◽  
Subjective Evaluation ◽  
Hearing Impaired ◽  
Spectral Subtraction ◽  
Reduction Algorithm ◽  
Subjective Testing ◽  
Noise Reduction Algorithm

This thesis is concerned with noise reduction in hearing aids. Hearing - impaired listeners and hearing - impaired users have great difficulty understanding speech in a noisy background. This problem has motivated the development and the use of noise reduction algorithms to improve the speech intelligibility in hearing aids. In this thesis, two noise reduction algorithms for single channel hearing instruments are presented, evaluated using objective and subjective tests. The first noise reduction algorithm, conventional Spectral Subtraction, is simulated using MATLAB 6.5, R13. The second noise reduction algorithm, Spectral Subtraction in wavelet domanin is introduced as well. This algorithm is implemented off line, and is compared with conventional Spectral Subtraction. A subjective evaluation demonstrates that the second algorithm has additional advantages in speech intelligibility, in poor listening conditions relative to conventional Spectral Subtraction. The subjective testing was performed with normal hearing listeners, at Ryerson University. The objective evaluation shows that the Spectral Subtraction in wavelet domain has improved Signal to Noise Ratio compared to conventional Spectral Subtraction.

scholarly journals Noise reduction in hearing aids using spectral subtraction techniques

2021 ◽  
Author(s):  
Fatos Myftari
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Speech Intelligibility ◽  
Single Channel ◽  
Subjective Evaluation ◽  
Hearing Impaired ◽  
Spectral Subtraction ◽  
Reduction Algorithm ◽  
Subjective Testing ◽  
Noise Reduction Algorithm

This thesis is concerned with noise reduction in hearing aids. Hearing - impaired listeners and hearing - impaired users have great difficulty understanding speech in a noisy background. This problem has motivated the development and the use of noise reduction algorithms to improve the speech intelligibility in hearing aids. In this thesis, two noise reduction algorithms for single channel hearing instruments are presented, evaluated using objective and subjective tests. The first noise reduction algorithm, conventional Spectral Subtraction, is simulated using MATLAB 6.5, R13. The second noise reduction algorithm, Spectral Subtraction in wavelet domanin is introduced as well. This algorithm is implemented off line, and is compared with conventional Spectral Subtraction. A subjective evaluation demonstrates that the second algorithm has additional advantages in speech intelligibility, in poor listening conditions relative to conventional Spectral Subtraction. The subjective testing was performed with normal hearing listeners, at Ryerson University. The objective evaluation shows that the Spectral Subtraction in wavelet domain has improved Signal to Noise Ratio compared to conventional Spectral Subtraction.

scholarly journals Speech quality evaluation of a sparse coding shrinkage noise reduction algorithm with normal hearing and hearing impaired listeners

2015 ◽  
Vol 327 ◽  
pp. 175-185 ◽  
Author(s):  
Jinqiu Sang ◽  
Hongmei Hu ◽  
Chengshi Zheng ◽  
Guoping Li ◽  
Mark E. Lutman ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Sparse Coding ◽  
Quality Evaluation ◽  
Normal Hearing ◽  
Speech Quality ◽  
Hearing Impaired ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

Evaluation of the sparse coding shrinkage noise reduction algorithm in normal hearing and hearing impaired listeners

2014 ◽  
Vol 310 ◽  
pp. 36-47 ◽  
Author(s):  
Jinqiu Sang ◽  
Hongmei Hu ◽  
Chengshi Zheng ◽  
Guoping Li ◽  
Mark E. Lutman ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Sparse Coding ◽  
Normal Hearing ◽  
Hearing Impaired ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

scholarly journals Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 319
Author(s):  
Chan-Rok Park ◽  
Seong-Hyeon Kang ◽  
Young-Jin Lee
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Total Variation ◽  
Parallel Imaging ◽  
Pulse Sequence ◽  
Reduction Algorithm ◽  
Median Filters ◽  
Reduction Techniques ◽  
Imaging Results ◽  
Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

scholarly journals Image Noise Reduction Algorithm for Digital Subtraction Angiography: Clinical Results

Radiology ◽  
2013 ◽  
Vol 269 (2) ◽  
pp. 553-560 ◽  
Author(s):  
Michael Söderman ◽  
Staffan Holmin ◽  
Tommy Andersson ◽  
Charlotta Palmgren ◽  
Draženko Babić ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Digital Subtraction Angiography ◽  
Clinical Results ◽  
Image Noise ◽  
Reduction Algorithm ◽  
Digital Subtraction ◽  
Image Noise Reduction ◽  
Noise Reduction Algorithm
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