Problem
Research questions and friction points this paper is trying to address.
SRIRs
Wasserstein metric
spherical harmonic domain
Spherical Harmonic Sliced Wasserstein Displacement Interpolation for Acoustic Source and Reflection Density Modeling
🤖 AI Summary
本文通过使用球谐域中的Wasserstein度量和位移方法，解决了移动声源的空间房间脉冲响应（SRIR）插值问题。
📝 Abstract
Spatial room impulse responses (SRIRs) capture directional distributions of acoustic sound-sources and their reflections. However, collecting SRIRs of moving sound-sources remains a challenge, requiring complex interpolations across measurements that account for multi-path spatial-temporal dynamics. This paper investigates the Wasserstein metric and displacement for evaluating interpolated SRIR echo densities in the spherical harmonic domain. We present novel sum-of-magnitude square expansions for efficiently fitting probability density functions, maximizing likelihood, inverse sampling, and computing spherical sliced Wasserstein interpolations. Experiments compare the Wasserstein displacements and metric to linear and geometric interpolations of SRIR image-source densities on a line-path, and demonstrate model-order reduction.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Spherical Harmonic
Wasserstein Displacement
Spatial Room Impulse Responses (SRIRs)
Sum-of-Magnitude Square Expansions
Model-Order Reduction
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