@article{TANG2025, 
author = {Zihan TANG and Yunrong LUO and Jincheng HU and Yurui YANG},
title = {EXPERIMENTAL DESIGN OF SOUND SOURCE LOCALIZATION BASED ON MICROPHONE ARRAYS AND NEURAL NETWORK},
year = {2025},
journal = {Physics and Engineering},
volume = {35},
number = {6},
pages = {190-199},
keywords = {microphone arrays, sound source localization, neural network, generalized cross-correlation time delay},
url = {https://www.sciopen.com/article/10.26599/PHYS.2025.9320630},
doi = {10.26599/PHYS.2025.9320630},
abstract = {This paper presents a sound source localization experimental setup that integrates microphone-array technology with neural networks and the generalized cross-correlation timedelay (GCC-TD) method. The system first preprocesses raw acoustic signals with a Kalman filter, then estimates the time-difference-of-arrival between microphones via GCC-TD, and finally employs a single-hidden-layer neural network to map these time differences onto two-dimensional coordinates, thereby pinpointing the sound source. Replacing conventional mathematical models with a neural network markedly mitigates systematic errors arising from ambient noise, sound-speed variations, and hardware latency, while simultaneously cutting computational complexity and memory requirements. Experimental results demonstrate that the apparatus offers high accuracy, low cost, and real-time display and logging of measurement data.}
}