no code implementations • 17 Apr 2024 • Eric Brandao, William Fonseca, Paulo Mareze, Carlos Resende, Gabriel Azzuz, Joao Pontalti, Efren Fernandez-Grande
This article proposes a method for estimating the sound absorption coefficient of a material sample by mapping the sound pressure, measured by a microphone array, to a distribution of monopoles along a line in the complex plane.
no code implementations • 10 Apr 2024 • Xenofon Karakonstantis, Efren Fernandez-Grande, Peter Gerstoft
In this study, we introduce a method for estimating sound fields in reverberant environments using a conditional invertible neural network (CINN).
no code implementations • 14 Mar 2024 • Marco Olivieri, Xenofon Karakonstantis, Mirco Pezzoli, Fabio Antonacci, Augusto Sarti, Efren Fernandez-Grande
Recent developments in acoustic signal processing have seen the integration of deep learning methodologies, alongside the continued prominence of classical wave expansion-based approaches, particularly in sound field reconstruction.
1 code implementation • 2 Jan 2024 • Xenofon Karakonstantis, Diego Caviedes-Nozal, Antoine Richard, Efren Fernandez-Grande
A method is presented for estimating and reconstructing the sound field within a room using physics-informed neural networks.
1 code implementation • 1 Aug 2023 • Xenofon Karakonstantis, Efren Fernandez-Grande
This paper presents a deep learning-based approach for the spatio-temporal reconstruction of sound fields using Generative Adversarial Networks (GANs).
1 code implementation • 24 Aug 2022 • Manuel Hahmann, Efren Fernandez-Grande
A suitable model can be difficult to determine when the spatial domain of interest is large compared to the wavelength or when spherical and planar wavefronts are present or the sound field is complex, as in the near-field.
no code implementations • 26 Jan 2021 • Michael J. Bianco, Sharon Gannot, Efren Fernandez-Grande, Peter Gerstoft
As far as we are aware, our paper presents the first approach to modeling the physics of acoustic propagation using deep generative modeling.