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Multi-channel low-frequency room equalization using perceptually motivated constrained optimization

机译:基于感知动机的约束优化的多通道低频房间均衡

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We consider the problem of multiple-loudspeaker low-frequency room equalization for a wide listening area, where the equalized loudspeaker is helped using the remaining ones. Using a spatial discretization of the listening area, we formulate the problem as a multipoint error minimization between desired and synthesized magnitude frequency responses. The desired response and cost function are formulated with a goal of capturing the room's spectral power profile, and penalizing strong resonances. Considering physical and psychoacoustical observations, we argue for the use of gain-limited, short, and well-localized equalization filters, with an additional delay for loudspeakers that help the equalized one. We propose a convex optimization framework for computing room equalization filters, where the mentioned filter requirements are incorporated as convex constraints. We verify the effectiveness of our equalization approach through simulations.
机译:我们考虑了在宽广的聆听区域中使用多扬声器低频房间均衡的问题,其中均衡的扬声器使用剩余的扬声器来帮助。使用聆听区域的空间离散化,我们将问题表述为期望幅度和合成幅度频率响应之间的多点误差最小化。制定期望的响应和成本函数的目的是捕获房间的频谱功率分布并惩罚强烈的共振。考虑到物理和心理声学观察,我们主张使用增益受限的,短的和局部良好的均衡滤波器,并为帮助均衡扬声器的扬声器增加额外的延迟。我们为计算室均衡滤波器提出了一个凸优化框架,其中提到的滤波器要求作为凸约束被并入。我们通过仿真验证了均衡方法的有效性。

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