TY  - JOUR
AU  - TANG, Zihan
AU  - LUO, Yunrong
AU  - HU, Jincheng
AU  - YANG, Yurui
PY  - 2025
TI  - EXPERIMENTAL DESIGN OF SOUND SOURCE LOCALIZATION BASED ON MICROPHONE ARRAYS AND NEURAL NETWORK
JO  - Physics and Engineering
SN  - 1009-7104
SP  - 190
EP  - 199
VL  - 35
IS  - 6
AB  - 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.
UR  - https://doi.org/10.26599/PHYS.2025.9320630
DO  - 10.26599/PHYS.2025.9320630