Environmental Sound Classification Based on Stacked Concatenated DNN using Aggregated Features-Reference-Cited by-同舟云学术

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Environmental Sound Classification Based on Stacked Concatenated DNN using Aggregated Features

Published:2021-09-16 Issue:11 Volume:93 Page:1287-1299
ISSN:1939-8018
Container-title:Journal of Signal Processing Systems
language:en
Short-container-title:J Sign Process Syst

Author:

Liu Chengwei,Hong Feng^ORCID,Feng Haihong,Zhai Yushuang,Chen Youyuan

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

the development fund for Shanghai talents

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11265-021-01702-x.pdf

Reference37 articles.

1. Chachada, S., Jay, C. C. (2014). Environmental sound recognition: A survey. Apsipa Transactions on Signal & Information Processing, 3.

2. Baum, E., Harper, M., Alicea, R., & Ordonez, C. (2018). Sound Identification for Fire-Fighting Mobile Robots. In 2018 Second IEEE international conference on robotic computing (IRC), pp.79–86.

3. Mydlarz, C., Salamon, J., & Bello, J. P. (2017). The implementation of low-cost urban acoustic monitoring devices. Applied Acoustics, 117, 207–218.

4. Fan, X., Sun, T., Chen, W., Fan, Q. (2020). Deep neural network based environment sound classification and its implementation on hearing aid app. Measurement, 159(9), 107790.

5. Su, Y., Zhang, K., Wang, J., & Madani, K. (2019). Environment sound classification using a two-stream CNN based on decision-level fusion. Sensors (Switzerland), 19(7), 1–15.

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