Abstract detail

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
Special Sessions > Nonstationary signal processing algorithms and applications
Final Paper
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.

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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