Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants-Reference-Cited by-同舟云学术

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Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants

Published:2019-07 Issue:1 Volume:146 Page:705-718
ISSN:0001-4966
Container-title:The Journal of the Acoustical Society of America
language:en
Short-container-title:The Journal of the Acoustical Society of America

Author:

Goehring Tobias¹,Keshavarzi Mahmoud²,Carlyon Robert P.¹,Moore Brian C. J.²

Affiliation:

1. Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom

2. Department of Experimental Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom

Funder

Action on Hearing Loss

EPSRC

Publisher

Acoustical Society of America (ASA)

Subject

Acoustics and Ultrasonics,Arts and Humanities (miscellaneous)

Link

http://asa.scitation.org/doi/pdf/10.1121/1.5119226

Cited by 65 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Using deep learning to improve the intelligibility of a target speaker in noisy multi-talker environments for people with normal hearing and hearing loss;The Journal of the Acoustical Society of America;2024-07-01

2. Deep learning restores speech intelligibility in multi-talker interference for cochlear implant users;Scientific Reports;2024-06-09

3. Recovering speech intelligibility with deep learning and multiple microphones in noisy-reverberant situations for people using cochlear implants;The Journal of the Acoustical Society of America;2024-06-01

4. UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features for Preventive, Personalized and Precision Medicine: A Narrative Review;Reviews in Cardiovascular Medicine;2024-05-22

5. Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method;Scientific Reports;2024-03-28

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