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A Survey: Neural Network-Based Deep Learning for Acoustic Event Detection

Xia, X., Togneri, R., Sohel, F., Zhao, Y. and Huang, D. (2019) A Survey: Neural Network-Based Deep Learning for Acoustic Event Detection. Circuits, Systems, and Signal Processing, 38 (8). pp. 3433-3353.

Link to Published Version: https://doi.org/10.1007/s00034-019-01094-1
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Abstract

Recently, neural network-based deep learning methods have been popularly applied to computer vision, speech signal processing and other pattern recognition areas. Remarkable success has been demonstrated by using the deep learning approaches. The purpose of this article is to provide a comprehensive survey for the neural network-based deep learning approaches on acoustic event detection. Different deep learning-based acoustic event detection approaches are investigated with an emphasis on both strongly labeled and weakly labeled acoustic event detection systems. This paper also discusses how deep learning methods benefit the acoustic event detection task and the potential issues that need to be addressed for prospective real-world scenarios.

Item Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Springer US
Copyright: © Springer Science+Business Media, LLC, part of Springer Nature 2019
URI: http://researchrepository.murdoch.edu.au/id/eprint/44836
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