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arXiv · 2407.18732

A Physics-Informed Neural Network-Based Approach for the Spatial Upsampling of Spherical Microphone Arrays

Federico Miotello·Ferdinando Terminiello·Mirco Pezzoli·Alberto Bernardini·Fabio Antonacci·Augusto Sarti
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Abstract

Spherical microphone arrays are convenient tools for capturing the spatial characteristics of a sound field. However, achieving superior spatial resolution requires arrays with numerous capsules, consequently leading to expensive devices. To address this issue, we present a method for spatially upsampling spherical microphone arrays with a limited number of capsules. Our approach exploits a physics-informed neural network with Rowdy activation functions, leveraging physical constraints to provide high-order microphone array signals, starting from low-order devices. Results show that, within its domain of application, our approach outperforms a state of the art method based on signal processing for spherical microphone arrays upsampling.

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Federico Miotello, Ferdinando Terminiello, Mirco Pezzoli, Alberto Bernardini, Fabio Antonacci, Augusto Sarti. 2024-07-26. A Physics-Informed Neural Network-Based Approach for the Spatial Upsampling of Spherical Microphone Arrays. https://arxiv.org/abs/2407.18732

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