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

被引:0
|
作者
Xianjun Xia
Roberto Togneri
Ferdous Sohel
Yuanjun Zhao
Defeng Huang
机构
[1] University of Western Australia,School of Electrical, Electronic and Computer Engineering
[2] Murdoch University,School of Engineering and Information Technology
关键词
Deep learning; Acoustic event detection; Strongly labeled; Weakly labeled;
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摘要
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.
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页码:3433 / 3453
页数:20
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