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Author:

Yue, Xiao (Yue, Xiao.) | Qu, Guangzhi (Qu, Guangzhi.) | Liu, Bo (Liu, Bo.) (Scholars:刘博) | Liu, Anyi (Liu, Anyi.)

Indexed by:

CPCI-S

Abstract:

Sound source detection and localization have a lot of practical uses in many industrial settings. Most of sound source direction detection algorithms in literature are designed to identify the angle of sound source in a 2D space. In this work, we propose to use convolutional neural networks to detect the sound source direction in a 3D space. This algorithm is based on the generalized cross correlation method with phase transform (GCC-PHAT) [1] to derive time delay of arrival (TDOA). By using a convolutional neural network model, this algorithm can be applied and deployed. In addition, by modifying GCC-PHAT formula, this approach also works of multiple sound sources detection. Simulation experimental results on single sound source and multiple sound sources detection show the proposed system could work in most situations.

Keyword:

Room impulse simulation Convolutional Neural Network GCC-PHAT Sound Source Direction Detection

Author Community:

  • [ 1 ] [Yue, Xiao]Oakland Univ, Comp Sci & Engn Dept, Rochester, MI 48063 USA
  • [ 2 ] [Qu, Guangzhi]Oakland Univ, Comp Sci & Engn Dept, Rochester, MI 48063 USA
  • [ 3 ] [Liu, Anyi]Oakland Univ, Comp Sci & Engn Dept, Rochester, MI 48063 USA
  • [ 4 ] [Liu, Bo]Beijing Univ Technol, Sch Software Engn, Fac Informat Technol, Beijing, Peoples R China

Reprint Author's Address:

  • [Yue, Xiao]Oakland Univ, Comp Sci & Engn Dept, Rochester, MI 48063 USA

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Source :

2018 FIRST IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE FOR INDUSTRIES (AI4I 2018)

Year: 2018

Page: 81-84

Language: English

Cited Count:

WoS CC Cited Count: 4

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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