DBSA-Net: Dual Branch Self-Attention Network for Underwater Acoustic Signal Denoising-Reference-Cited by-同舟云学术

DBSA-Net: Dual Branch Self-Attention Network for Underwater Acoustic Signal Denoising

Published:2023 Issue: Volume:31 Page:1851-1865
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Zhou Aolong¹^ORCID,Zhang Wen²^ORCID,Xu Guojun³^ORCID,Li Xiaoyong¹^ORCID,Deng Kefeng¹^ORCID,Song Junqiang¹^ORCID

Affiliation:

1. College of Computer Science and Technology, and College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China

2. Strategic Evaluation and Consultation Center of Academy of Military Sciences, Beijing, China

3. College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

http://xplorestaging.ieee.org/ielx7/6570655/9970249/10122557.pdf?arnumber=10122557

Reference56 articles.

1. Interactive Speech and Noise Modeling for Speech Enhancement

2. An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation

3. Evaluation of a segmental SNR measure as an indicator of the quality of ADPCM coded speech

4. Divide and Conquer: A Deep CASA Approach to Talker-Independent Monaural Speaker Separation

5. Fullsubnet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement

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