A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions-Reference-Cited by-同舟云学术

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A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions

Published:2018-09 Issue:3 Volume:144 Page:1627-1637
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:

Zhao Yan,Wang DeLiang,Johnson Eric M.,Healy Eric W.

Funder

National Institute on Deafness and Other Communication Disorders

Publisher

Acoustical Society of America (ASA)

Subject

Acoustics and Ultrasonics,Arts and Humanities (miscellaneous)

Link

http://asa.scitation.org/doi/pdf/10.1121/1.5055562

Cited by 27 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. 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

2. Contributions of temporal envelope and temporal fine structure to segregation of Lombard speech from background noise;Acoustical Science and Technology;2024-01-01

3. On the Predictive Power of Objective Intelligibility Metrics for the Subjective Performance of Deep Complex Convolutional Recurrent Speech Enhancement Networks;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

4. Speech Dereverberation Based on Self-supervised Residual Denoising Autoencoder with Linear Decoder;Proceedings in Adaptation, Learning and Optimization;2024

5. Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users;Frontiers in Medical Engineering;2023-11-15

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