Improving sound field analysis with multiscale sparse wave methods
Multiscale Generalized Sparse Plane Wave Decomposition in the Spherical Harmonic Domain
Sound
Summary
Understanding how sound travels and where it comes from is important for many audio technologies. The authors improved a method called sparse plane wave decomposition, which breaks down complex sound fields into simpler parts for easier analysis. They introduced a way to do this at multiple scales using a better mathematical tool called an optimal spherical kernel. Their new approach helps recover sound features more accurately and quickly, as shown in computer simulations.
What this means in practice
- •For audio engineers: Enhance real-time localization of sound sources in 3D spaces using improved plane wave decomposition.
- •For acoustic device developers: Improve sound separation algorithms in devices like hearing aids or smart speakers with multiscale sparse decompositions.
Authors
Huseyin Hacihabiboglu
Abstract
Sparse plane wave decomposition (SPWD) is a physics-driven model-based approach for analyzing sound fields that is suitable for real-time operation. SPWD is used in different contexts such as direction of arrival (DOA) estimation and sound field separation. SPWD employs spherical Dirichlet kernels to decompose sound fields represented as steered response maps into a finite number of plane waves using sparse recovery techniques. This article proposes a multiscale generalized sparse plane wave decomposition approach that uses an optimal spherical kernel and a multiscale sparse decomposition method to improve recovery performance. The utility of the proposed approach is shown by comparisons with the original SPWD approach via extensive numerical simulations.