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Parametric Ambisonic Encoding of Arbitrary Microphone Arrays

Leo McCormack (Aalto University); Archontis Politis (Tampere University); Raimundo Gonzalez Diaz (Aalto University); Tapio Lokki (Aalto University); Ville T Pulkki (Aalto University)

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09 Jun 2023

This article proposes a parametric signal-dependent method for the task of encoding microphone array signals into Ambisonic signals. The proposed method is presented and evaluated in the context of encoding a simulated seven-sensor microphone array, which is mounted on an augmented reality headset device. Given the inherent flexibility of the Ambisonics format, and its popularity within the context of such devices, this array configuration represents a potential future use case for Ambisonic recording. However, due to its irregular geometry and non-uniform sensor placement, conventional signal-independent Ambisonic encoding is particularly limited. The primary aims of the proposed method are to obtain Ambisonic signals over a wider frequency band-width, and at a higher spatial resolution, than would otherwise be possible through conventional signal-independent encoding. The proposed method is based on a multi-source sound-field model and employs spatial filtering to divide the captured sound-field into its individual source and directional ambient components, which are subsequently encoded into the Ambisonics format at an arbitrary order. It is demonstrated through both objective and perceptual evaluations that the proposed parametric method outperforms conventional signal-independent encoding in the majority of cases.

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