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

scholarly journals A single microphone noise reduction algorithm based on the detection and reconstruction of spectro-temporal features

2015 ◽  
Vol 471 (2184) ◽  
pp. 20150309 ◽  
Author(s):  
Tyler Lee ◽  
Frédéric Theunissen
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Background Noise ◽  
Speech Intelligibility ◽  
State Of The Art ◽  
Reduction Algorithm ◽  
Temporal Correlations ◽  
Temporal Features ◽  
Wide Range ◽  
Noise Reduction Algorithm

Animals throughout the animal kingdom excel at extracting individual sounds from competing background sounds, yet current state-of-the-art signal processing algorithms struggle to process speech in the presence of even modest background noise. Recent psychophysical experiments in humans and electrophysiological recordings in animal models suggest that the brain is adapted to process sounds within the restricted domain of spectro-temporal modulations found in natural sounds. Here, we describe a novel single microphone noise reduction algorithm called spectro-temporal detection–reconstruction (STDR) that relies on an artificial neural network trained to detect, extract and reconstruct the spectro-temporal features found in speech. STDR can significantly reduce the level of the background noise while preserving the foreground speech quality and improving estimates of speech intelligibility. In addition, by leveraging the strong temporal correlations present in speech, the STDR algorithm can also operate on predictions of upcoming speech features, retaining similar performance levels while minimizing inherent throughput delays. STDR performs better than a competing state-of-the-art algorithm for a wide range of signal-to-noise ratios and has the potential for real-time applications such as hearing aids and automatic speech recognition.

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.

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.

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.

A coherence-based noise reduction algorithm for binaural hearing aids

2014 ◽  
Vol 58 ◽  
pp. 101-110 ◽  
Author(s):  
Nima Yousefian ◽  
Philipos C. Loizou ◽  
John H.L. Hansen
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Binaural Hearing ◽  
Reduction Algorithm ◽  
Binaural Hearing Aids ◽  
Noise Reduction Algorithm
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