An intrusive method for estimating speech intelligibility from noisy and distorted signals-Reference-Cited by-同舟云学术

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An intrusive method for estimating speech intelligibility from noisy and distorted signals

Published:2021-09 Issue:3 Volume:150 Page:1762-1778
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:

Mamun Nursadul¹,Zilany Muhammad S. A.²,Hansen John H. L.¹,Davies-Venn Evelyn E.³

Affiliation:

1. Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, Texas 75080, USA

2. Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar

3. Department of Speech-Language-Hearing Sciences, University of Minnesota, Minneapolis, Minnesota 55455, USA

Publisher

Acoustical Society of America (ASA)

Subject

Acoustics and Ultrasonics,Arts and Humanities (miscellaneous)

Link

https://asa.scitation.org/doi/pdf/10.1121/10.0005899

Cited by 6 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. Speech Enhancement for Cochlear Implant Recipients Using Deep Complex Convolution Transformer With Frequency Transformation;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. CFTNet: Complex-valued Frequency Transformation Network for Speech Enhancement;INTERSPEECH 2023;2023-08-20

3. A T-F Masking based Monaural Speech Enhancement using U-Net Architecture;2023 International Conference on Electrical, Computer and Communication Engineering (ECCE);2023-02-23

4. A Joint Bandwidth Expansion and Speech Enhancement Approach Using Deep Neural Network;2023 International Conference on Electrical, Computer and Communication Engineering (ECCE);2023-02-23

5. Deep Learning-Based Non-Intrusive Multi-Objective Speech Assessment Model With Cross-Domain Features;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023

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