Neural Optimization Of Geometry And Fixed Beamformer For Linear Microphone Arrays
Longfei Yan, Weilong Huang, W. Bastiaan Kleijn, Thushara D. Abhayapala
Abstract
Fixed beamforming based on uniform linear microphone arrays often suffers from non-optimal performance for broadband signals. This paper addresses the issue by jointly optimizing the array geometry and spatial filters through a neural network based model. The model, composed of two feed forward neural networks, is optimized in an end-to-end manner. It satisfies the distortionless constraint in the look direction. Experimental results show that the proposed model outperforms the previous state-of-the-art fixed beamformer with overall better scores. Moreover, the proposed model can control the tradeoff between Directivity Factor (DF) and White Noise Gain (WNG) in a flexible way.
BibTeX
@inproceedings{icassp2023_neuraloptimizati,
title = {Neural Optimization Of Geometry And Fixed Beamformer For Linear Microphone Arrays},
author = {Longfei Yan and Weilong Huang and W. Bastiaan Kleijn and Thushara D. Abhayapala},
booktitle = {ICASSP 2023},
year = {2023}
}