Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators.

ABSTRACT: We address the challenge of acoustic simulations in three-dimensional (3D) virtual rooms with parametric source positions, which have applications in virtual/augmented reality, game audio, and spatial computing. The wave equation can fully describe wave phenomena such as diffraction and interference. However, conventional numerical discretization methods are computationally expensive when simulating hundreds of source and receiver positions, making simulations with parametric source positions impractical. To overcome this limitation, we propose using deep operator networks to approximate linear wave-equation operators. This enables the rapid prediction of sound propagation in realistic 3D acoustic scenes with parametric source positions, achieving millisecond-scale computations. By learnin

SUBMITTER: Borrel-Jensen N 

PROVIDER: S-EPMC10786273 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature