用球谐函数模拟房间声学，实现实时头动下的沉浸式音频渲染。
SHroom: A Python Framework for Ambisonics Room Acoustics Simulation and Binaural Rendering
- 将声源图像投影到球谐函数基，构建可组合的音频处理流程
- 在N=5时达到2.02dB的频谱距离，接近人耳可察觉阈值
- 支持实时头部转动，每帧延迟小于1毫秒，适合虚拟现实应用
SHroom 是一个开源的 Python 库，用于基于阿姆比森音（Ambisonics）的房间声学仿真，可通过 pip install pyshroom 安装。该框架将图像源贡献投影到球谐函数（Spherical Harmonics, SH）基上，实现了可组合的双耳解码、球面阵列仿真和实时头部旋转。与 N=30 的参考基准相比，使用幅度最小二乘法（MagLS）的 SHroom 在 N=5 时达到 2.02 dB 的对数谱距离（LSD），处于 1–2 dB 的可察觉差异（JND）范围内；其一次性固定解码机制在多声源（K=1 至 8）场景下性能提升显著，处理速度从 7 倍降至 3.1 倍延迟。对于动态头部旋转，SHroom 采用 Wigner-D 乘法，每帧延迟低于 1 毫秒，是目前唯一具备实时架构可行性的解决方案。
原文摘要 · Abstract (English)
Spherical Harmonics ROOM), an open-source Python library for room acoustics simulation using Ambisonics, available at https://github.com/Yhonatangayer/shroom and installable via \texttt{pip install pyshroom}. \textbf{shroom} projects image-source contributions onto a Spherical Harmonics (SH) basis, yielding a composable pipeline for binaural decoding, spherical array simulation, and real-time head rotation. Benchmarked against \texttt{pyroomacoustics} with an $N=30$ reference, \textbf{shroom} with Magnitude Least Squares (MagLS) achieves perceptual transparency (2.02~dB Log Spectral Distance (LSD) at $N=5$, within the 1--2~dB Just Noticeable Difference (JND)) while its fixed-once decode amortises over multiple sources ($K=1$-to-$8$: slowdown narrows from $7\times$ to $3.1\times$). For dynamic head rotation, \textbf{shroom} applies a Wigner-D multiply at $<1$~ms/frame, making it the only architecturally viable real-time choice.
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