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

Xianjun Xia, Roberto Togneri, Ferdous Sohel, Yuanjun Zhao, Defeng Huang

Research output: Contribution to journalArticle

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.

Original languageEnglish
JournalCircuits, Systems, and Signal Processing
DOIs
Publication statusE-pub ahead of print - 21 Mar 2019

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Event Detection
Acoustics
Neural Networks
Neural networks
Speech Processing
Speech Signal
Computer Vision
Computer vision
Pattern Recognition
Pattern recognition
Signal Processing
Signal processing
Learning
Deep learning
Scenarios

Cite this

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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.",
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AU - Zhao, Yuanjun

AU - Huang, Defeng

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AB - 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.

KW - Acoustic event detection

KW - Deep learning

KW - Strongly labeled

KW - Weakly labeled

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