Sound field navigation with virtual higher-order sound sources using complex greedy pursuit algorithm

Abstract

As the Virtual Reality (VR) and metaverse industries continue to expand rapidly, there is a growing need to capture and recreate real-world experiences in immersive audio-visual scenes. Sound field translation, which activates equivalent virtual sources to recreate spatial sound fields, enables users to navigate through these scenes seamlessly. However, combining recordings from different microphones and processing mixed fields of exterior and interior sources present significant challenges. This paper introduces a novel method for virtual navigation by sparsely decomposing complex sound fields using distributed virtual higher-order sound sources and an iterative complex greedy pursuit algorithm. By combining spatially separated microphone recordings, the technique identifies its sparse representation with several higher-order virtual sources. This process effectively decomposes the complex sound field into a grid of higher-order sources, leveraging the power of the complex greedy pursuit algorithm. Through extensive experimentation, we demonstrate the suitability of our method for applications such as VR navigation and sound field reproduction with binaural devices. The results showcase enhanced realism and accuracy, offering users a truly immersive audio experience in virtual environments. As the demand for realistic audio-visual scenes grows, this innovative approach holds promise for advancing VR technology and enriching user experiences in the metaverse.