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    ARTICLE

    Deep Learning-based Environmental Sound Classification Using Feature Fusion and Data Enhancement

    Rashid Jahangir1,*, Muhammad Asif Nauman2, Roobaea Alroobaea3, Jasem Almotiri3, Muhammad Mohsin Malik1, Sabah M. Alzahrani3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1069-1091, 2023, DOI:10.32604/cmc.2023.032719 - 22 September 2022

    Abstract Environmental sound classification (ESC) involves the process of distinguishing an audio stream associated with numerous environmental sounds. Some common aspects such as the framework difference, overlapping of different sound events, and the presence of various sound sources during recording make the ESC task much more complicated and complex. This research is to propose a deep learning model to improve the recognition rate of environmental sounds and reduce the model training time under limited computation resources. In this research, the performance of transformer and convolutional neural networks (CNN) are investigated. Seven audio features, chromagram, Mel-spectrogram, tonnetz,… More >

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