发表机构
NuSpace Audio（NuSpace Audio）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出时变指数卷积方法，将高斯噪声和脉冲响应转换为混响及修正频谱衰减场，推导两种快速递归算法并扩展到球谐域，以生成方向相关混响，实验验证了计算性能和分布外生成效果。
AI 中文摘要
球谐编码的声学声场捕捉了房间脉冲响应的方向特性，这些特性对于精确的空间音频再现非常有用。然而，多麦克风测量和数值模拟的高成本促使人们寻找替代的数据增强和合成数据生成方法，以补充小型数据集。本文介绍了时变指数卷积方法，这些方法分别将高斯噪声和脉冲响应转换为混响场和修正的频谱衰减场。我们推导了两种递归且快速的卷积算法，这些算法扩展到球谐域，用非平稳高斯过程建模平滑的混响时间分布，并实现了最优滤波器设计。实验评估了计算性能，并验证了分布外生成的脉冲响应。
英文摘要
Spherical harmonic encoded acoustic sound-fields capture directional characteristics of room impulse responses that are useful for accurate spatial audio reproduction. However, high costs of multi-microphone measurements and numerical simulations motivate alternative data-set augmentation and synthetic data generation methods that supplement small collections. This paper introduces time-varying exponentiated convolution methods that transform both Gaussian noise and impulse responses into reverberation and modified spectral-decay fields respectively. We derive two recursive and fast convolution algorithms that extend into the spherical harmonic domain, model smooth reverberation time distributions with non-stationary Gaussian processes, and realize an optimal filter design. Experiments evaluate computational performance, and validate out-of-distribution generated impulse responses.
CommentsAccepted to proceedings at Audio Engineering Society Convention Nashville 2027
