Journal of Guangxi Normal University(Natural Science Edition) ›› 2023, Vol. 41 ›› Issue (2): 1-18.doi: 10.16088/j.issn.1001-6600.2022083002

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Review of Sound Event Detection

YANG Shuozhen1, ZHANG Long1*, WANG Jianhua2, ZHANG Hengyuan1   

  1. 1. College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China;
    2. College of Computer Information Engineering, Guangzhou Huali Vocational College of Science and Technology, Guangzhou Guangdong 511325, China
  • Received:2022-08-30 Revised:2022-10-25 Online:2023-03-25 Published:2023-04-25

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Abstract: Sound event detection technology can identify the types of events in an audio segment and mark the start and end time of each event. It has great potential in application scenarios such as smart cities, medical monitoring, and wildlife protection. It is an important issue in the field of machine hearing subject research. Firstly, this paper reviews sound event detection methods from two aspects of supervised learning and semi-supervised learning. Then, summarizes and analyzes the features, detection models and their performances used in existing research. For supervised learning, machine learning methods and deep learning methods are highlighted. For semi-supervised learning, four effective methods based on mean teacher, co-training, multi-scale convolution and attention mechanism are summarized. Finally, common datasets and evaluation metrics are introduced, and possible future research directions are discussed, including voice separation preprocessing, domain adaptation of synthetic data and real data, self-attention model optimization, feature selection and fusion, streaming system modeling and other issues.

Key words: sound event detection, machine learning, deep learning, neural networks, supervised learning, semi-supervised learning

CLC Number: 

  • TN912.3
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