Reconstruction of Sound Field through Diffusion Models

arXiv:2312.08821v2 Announce Type: replace-cross
Abstract: Reconstructing the sound field in a room is an important task for several applications, such as sound control and augmented (AR) or virtual reality (VR). In this paper, we propose a data-driven generative model for reconstructing the magnitude of acoustic fields in rooms with a focus on the modal frequency range. We introduce, for the first time, the use of a conditional Denoising Diffusion Probabilistic Model (DDPM) trained in order to reconstruct the sound field …

abstract applications arxiv control cs.lg cs.sd data data-driven diffusion diffusion models eess.as eess.sp fields focus generative paper reality room sound through type virtual virtual reality