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 journalArticlepeer-review

15 Citations (Scopus)


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
Pages (from-to)3433-3453
Number of pages21
JournalCircuits, Systems, and Signal Processing
Issue number8
Publication statusPublished - 15 Aug 2019


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