NEURAL OPTIMIZATION OF GEOMETRY AND FIXED BEAMFORMER FOR LINEAR MICROPHONE ARRAYS

Longfei Felix Yan, Weilong Huang, W. Bastiaan Kleijn, Thushara 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.