Convex Regularizations for the Simultaneous Recording of Room Impulse Responses
Convex Regularizations for the Simultaneous Recording of Room Impulse Responses
复制标题
用于同时记录房间脉冲响应的凸正则化
DOI：
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发表时间：
2014
影响因子：
5.4
通讯作者：
R. Gribonval
中科院分区：
文献类型：
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作者：
Alexis Benichoux;L. Simon;E. Vincent;R. Gribonval
我们建议通过在多个扬声器上同时播放已知源信号来获取大量房间脉冲响应（RIR）。然后，我们通过凸优化算法来估计 RIR，该算法使用促进稀疏性和/或指数幅度包络的凸惩罚。我们在现实世界的录音中验证了这种方法。即使当记录的样本数量小于要估计的 RIR 样本数量时，所提出的算法也可以以合理的精度估计 RIR，从而与最先进的 RIR 采集技术相比，加快记录过程。此外，促进稀疏性和指数幅度包络的惩罚在参数选择的鲁棒性方面提供了最佳结果，从而巩固了有利于 RIR 估计稀疏正则化的证据。最后，分析和评估发射信号选择的影响。
We propose to acquire large sets of room impulse responses (RIRs) by simultaneously playing known source signals on multiple loudspeakers. We then estimate the RIRs via a convex optimization algorithm using convex penalties promoting sparsity and/or exponential amplitude envelope. We validate this approach on real-world recordings. The proposed algorithm makes it possible to estimate the RIRs to a reasonable accuracy even when the number of recorded samples is smaller than the number of RIR samples to be estimated, thereby leading to a speedup of the recording process compared to state-of-the-art RIR acquisition techniques. Moreover, the penalty promoting both sparsity and exponential amplitude envelope provides the best results in terms of robustness to the choice of its parameters, thereby consolidating the evidence in favor of sparse regularization for RIR estimation. Finally, the impact of the choice of the emitted signals is analyzed and evaluated.