Comments on "Primary-Ambient Extraction Using Ambient Spectrum Estimation for Immersive Spatial Audio Reproduction"

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Haisheng Lu, Jiangnan Liang, Chuang Shi

Published: 2024, Last Modified: 04 Nov 2025IEEE ACM Trans. Audio Speech Lang. Process. 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In the above paper, He et al. propose a primary-ambient extraction method using ambient phase estimation with a sparsity constraint (APES). The primary-ambient extraction problem is formulated as a $L1$-norm minimization of the primary component with respect to the phase of the ambient component, based on a stereo signal model they have assumed. Discrete searching (DS) is proposed as the approach for solving the APES in each time-frequency bin, which is computationally complicated and potentially imprecise. This correspondence provides an analytical solution to the APES by exploring the geometric relation between the primary and ambient components in a rotated coordinate.