发表机构
Friedrich-Alexander-Universität Erlangen-Nürnberg; Aalto University（埃尔朗根-纽伦堡弗里德里希-亚历山大大学; 阿尔托大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出基于IS-NMF的参数化方法，联合估计RIRs中的公共斜率衰减率和空间幅度，通过贡献加权SAGE加速优化，在合成和实测数据上验证了准确性与高效性。
AI 中文摘要
我们将从房间冲激响应（RIRs）中联合估计公共斜率衰减率和幅度的问题，建模为以Itakura-Saito散度作为损失函数的参数化非负矩阵分解（IS-NMF）。在每个短时傅里叶变换频率点上的估计，可直接从RIR功率中生成详细的混响时间（RT）曲线，无需反向积分。标准的空间交替广义期望最大化（SAGE）算法为幅度更新提供了闭式解，并为每个衰减率更新产生一个凸子问题。为加速估计，我们引入了贡献加权SAGE，该算法强调每个分量对建模功率贡献较大的观测。合成数据实验表明，该方法能准确恢复分离良好的衰减，且损失下降速度比标准SAGE更快。应用于实测耦合房间RIRs，可得到随频率变化的RT曲线，并揭示共享衰减分量的互补时空贡献。
英文摘要
We formulate joint estimation of common-slope decay rates and amplitudes from room impulse responses (RIRs) as parameterized nonnegative matrix factorization with the Itakura--Saito divergence as the loss function (IS-NMF). Estimation at each short-time Fourier transform frequency bin produces detailed reverberation time (RT) curves directly from RIR powers with no backward integration needed. Standard space-alternating generalized expectation-maximization (SAGE) algorithm yields closed-form amplitude updates and a convex subproblem for each decay rate update. To accelerate estimation, we introduce contribution-weighted SAGE, which emphasizes observations where each component contributes strongly to the modeled power. Experiments with synthetic data show accurate recovery of well-separated decays and faster loss reduction than standard SAGE. Application to measured coupled-room RIRs yields frequency-dependent RT curves and reveals complementary space-time contributions of the shared decay components.
Comments5 pages, 5 figures. Submitted to ICASSP 2027
