Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

October 4, 2024


Pages


DOI

Article

Method and practice of microphone array speech source localization based on sound propagation modeling


Authors

Gang Meng Affiliation:
Shanghai University of Engineering Science, Shanghai, 201620, China.
, Chao Yang Affiliation:
Shanghai University of Engineering Science, Shanghai, 201620, China.
, Hui Guo Affiliation:
Shanghai University of Engineering Science, Shanghai, 201620, China.
and Yansong Wang Affiliation:
Shanghai University of Engineering Science, Shanghai, 201620, China.


Abstract

This paper realizes the speech source localization for microphone arrays based on the sound propagation model. According to the actual environment and location of the sound source, this paper divides the sound source into far-field source and near-field source and constructs the far-field sound model and near-field sound model applicable to the microphone array. The TDOA time-delayed localization algorithm is employed to locate the voice source of the microphone array by judging the sound far and near the field. In the localization test, this paper selects microphones to form an array according to the actual needs and preprocesses the sound signal data required for practice. The preprocessing data and sound source localization practice prove that the microphone array speech source localization algorithm used in this paper can effectively estimate the actual position of the sound source, and the absolute error between its estimated sound source position and the actual sound source position is only about 0.3m.


Keywords

Far-field sound model, Near-field sound model, Time delay algorithm, Speech source localization, Microphone array, 97P20


Citation

Meng, G., Yang, C., Guo, H., & Wang, Y. (2024). Method and practice of microphone array speech source localization based on sound propagation modeling. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-2681
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