Sound field reconstruction: towards large-scale spatial sensing

Abstract

Over the last couple of decades, sound field analysis and reconstruction methods have enabled us to observe and better understand diverse acoustic phenomena, from jetnoise to the sound of historical violins. In a broad sense, sound field reconstruction methods consist of capturing the spatial properties of sound, in order to visualize, analyze, reproduce, or manipulate the sound field in various ways. Fueled by advances in instrumentation and signal processing, these methods have had a profound impact in the field of acoustics and have been widely adopted in areas like vibro-acoustics, spatial audio, room acoustics, materials and electroacoustics -among others. In this talk we discuss new approaches for capturing and reconstructing sound fields in space, motivated by some of the longstanding challenges in the field. Specifically, we consider: 1) novel sensing methods, with a focus on optical remote sensing and the acousto-optic interaction, to measure sound using light, 2) physical models for largescale sound field visualization/reconstruction and 3) Deep Learning approaches for augmenting conventional acoustic measurements. Finally, we share an outlook of this multifaceted and increasingly relevant domain of acoustics.