AI 中文总结
提出基于最优传输重心的框架，从已知源的镜像源点云插值新源位置的点云，无需重复测量，实现高效灵活的房间声学建模。
AI 中文摘要
房间冲激响应可以通过镜像源模型（ISM）利用物理源的镜像源点云（ISPC）进行估计。然而，由于源移动会改变ISPC，在新源位置估计ISPC通常需要重复的声学测量。我们提出一个最优传输（OT）重心框架，从已知源的ISPC插值出新源位置的ISPC。该方法联合估计镜像源关联和新位置的ISPC。OT地面代价利用了镜像源与其物理源经历相同位移这一性质。该方法在基于网格和无支撑配置中均得以实现。无支撑方法通过交替进行跨ISPC的镜像源关联识别与目标镜像源位置细化，来解决由此产生的非凸联合估计问题。这使得无需重复测量即可进行ISPC插值，从而促进高效且灵活的房间声学建模。
英文摘要
Room impulse responses can be estimated via the image source model (ISM) using the image source point cloud (ISPC) of a physical source. However, because the source movement changes the ISPC, estimating the ISPC at a new source position typically requires repeated acoustic measurements. We propose an optimal transport (OT) barycenter framework to interpolate the ISPC of a new source location from ISPCs of known sources. The method jointly estimates image-source associations and the ISPC at the new location. The OT ground cost exploits the property that the image sources undergo the same displacement as their physical sources. This approach is realized for both grid-based and support-free configurations. The support-free method addresses the resulting nonconvex joint estimation problem by alternating between identifying image-source associations across the ISPCs and refining the target image-source locations. This enables the interpolation of ISPCs without repeated measurements, facilitating efficient and flexible room-acoustic modeling.
CommentsSubmitted to ICAASP 2027
