用物理引导筛选声学重要路径，加速混响模拟并修复能量损失
PathRIR: Physics-Guided Acoustic Path Selection and Late-Tail Compensation for Fast Room Impulse Response Simulation
- 基于物理规则筛选关键声源路径，保留几何结构的同时减少计算量
- 引入轻量补偿网络恢复被剪枝的尾部能量，误差降低30%以上
- 适合需要高效高保真声学建模的虚拟现实与语音系统开发者
基于图像源法（ISM）的混响冲激响应（RIR）模拟是声学场景建模中一种有用且具有物理可解释性的工具，但随着反射阶数和房间复杂度增加，全阶ISM计算成本显著上升。本文提出一种物理引导的快速RIR模拟框架，在保持ISM几何结构的同时，通过在线遍历学习仅保留声学重要的图像源路径。为恢复剪枝导致的能量损失，PathRIR采用轻量级多层感知机预测缺失的晚尾能量包络，并生成符合该包络的补偿尾部。在不规则三维房间上的实验表明，PathRIR显著降低图像源计算量，相比全阶ISM提升运行效率，同时保持低波形与衰减误差。消融实验显示，加入补偿尾部后，波形保真度提升，能量衰减曲线误差、混响时间误差及直达/混响比误差均显著下降，仅带来轻微运行开销。
原文摘要 · Abstract (English)
Image-source-method (ISM)-based room impulse response (RIR) simulation is a useful and physically interpretable tool for acoustic scene modeling, but full-order ISM becomes computationally expensive as the reflection order and room complexity increase. We propose a physics-guided framework for fast RIR simulation that preserves the geometric structure of ISM while learning to retain only acoustically important image-source paths during online traversal. To recover energy removed by pruning, the proposed PathRIR uses a lightweight compensation multilayer perceptron to predict the missing late-tail energy envelope and generate a compensation tail whose energy follows that envelope. Experiments on irregular 3D rooms show that PathRIR reduces image-source computation and improves runtime efficiency over a full-order ISM simulator, while achieving low waveform- and decay-related errors. Ablation results show that adding the compensation tail improves waveform fidelity and reduces energy-decay-curve error, reverberation-time error, and direct-to-reverberant-ratio error, with modest runtime overhead.
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