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Related Experiment Video

Updated: Nov 19, 2025

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
04:32

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Published on: December 20, 2024

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A feature-based data association method for multiple acoustic source localization in a distributed microphone array.

Xudong Dang1, Hongyan Zhu1

  • 1Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

The Journal of the Acoustical Society of America
|January 30, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient method for locating multiple sound sources in 3D using time difference of arrival (TDOA) and interchannel phase difference (IPD) features. It effectively solves the data association problem for distributed microphone arrays.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Computational Audition

Background:

  • Multisource localization using time difference of arrival (TDOA) faces challenges with data association, where correctly matching TDOA estimates to sources is difficult.
  • Existing two-dimensional localization methods often become computationally complex when extended to three dimensions (3D).

Purpose of the Study:

  • To propose an efficient, feature-based approach for multisource localization in 3D using distributed microphone arrays.
  • To address the data association problem in TDOA-based localization.
  • To reduce computational complexity compared to traditional 3D extensions.

Main Methods:

  • Generating features using interchannel phase difference (IPD) information to represent source assignments across frequency bins and time frames.
  • Solving the data association problem by correlating similar IPD features across microphone pairs via successive 2D assignment problems.
  • Estimating source locations by applying a single-source localization algorithm to the resolved TDOA combinations.

Main Results:

  • The proposed method effectively handles the data association problem in multisource localization.
  • The approach enables accurate 3D localization using distributed microphone arrays.
  • The feature-based method demonstrates efficiency and reduced computational complexity.

Conclusions:

  • The developed feature-based approach provides an efficient solution for 3D multisource localization.
  • This method successfully addresses the critical data association challenge in TDOA localization.
  • The approach is validated through simulations and real-world acoustic data.