210 / 2021-03-31 22:57:29
Acoustic-Net: A Novel Neural Network for Sound Localization and Quantification
Beamforming,Acoustic Imaging,Neural Network,Array Signal Processing,Sound Localization
终稿
Guanxing Zhou / XiaMen University
Hao Liang / XiaMen University
Xinghao Ding / XiaMen University
Xiaotong Tu / XiaMen University
Yue Huang / XiaMen University
Saqlain Abbas / Department of Mechanical Engineering, University of Engineering and Technology(UET)Lahore( Narowal campus)
Acoustic source localization has been applied in different fields, such as aeronautics and ocean science, generally using multiple microphones array data to reconstruct the source location. However, the model-based beamforming methods fail to achieve the high-resolution of conventional beamforming maps. Deep neural networks are also appropriate to locate the sound source, but in general, these methods with complex network structures are hard to be recognized by hardware. In this paper, a novel neural network, termed the Acoustic-Net, is proposed to locate and quantify the sound source simply using the original signals. The experiments demonstrate that the proposed method significantly improves the accuracy of sound source prediction and the computing speed, which may generalize well to real data. The code and trained models are available at https://github.com/JoaquinChou/Acoustic-Net.
重要日期
  • 会议日期

    11月01日

    2022

    11月03日

    2022

  • 10月30日 2022

    初稿截稿日期

  • 11月09日 2022

    注册截止日期

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Qingdao University of Technology
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