Automatic Respiratory Sound Classification Via Multi-Branch Temporal Convolutional Network

Author:

Zhao Ziping1,Gong Zhen1,Niu Mingyue1,Ma Jiali1,Wang Haishuai2,Zhang Zixing3,Li Ya4

Affiliation:

1. Tianjin Normal University,College of Computer and Information Engineering,Tianjin,China

2. Fairfield University,Department of Computer Science and Engineering,USA

3. GLAM – Group on Language, Audio, & Music,Imperial College London,UK

4. Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China

Funder

National Natural Science Foundation of China

Beijing University of Posts and Telecommunications

National Laboratory of Pattern Recognition

Publisher

IEEE

Cited by 17 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. Modeling Quasi-Periodic Dependency via Self-Supervised Pre-Training for Respiratory Sound Classification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. GaP-Aug: Gamma Patch-Wise Correction Augmentation Method for Respiratory Sound Classification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Multi-View Spectrogram Transformer for Respiratory Sound Classification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. E-DOCRNet: A multi-feature fusion network for dog bark identification;Applied Acoustics;2024-04

5. A lightweight feature extraction technique for deepfake audio detection;Multimedia Tools and Applications;2024-01-25

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