Optimizing Higher-Order Directional Audio Coding with Adaptive Mixing and Energy Matching for Ambisonic Compression and Upmixing

Abstract

In order to transmit sound-scenes encoded into the higher-order Ambisonics (HOA) format to low-bandwidth devices, transmission codecs are needed to reduce data requirements. Recently, the model-based higher-order directional audio coding (HO-DirAC) method was formulated for HOA input to HOA output. Compression is achieved by reducing the number of audio transport channels through spatial discretization. These transport channels are then used to reconstruct the scene on the receiving end based on accompanying spatial metadata. This reconstructed scene may also be optionally upmixed to a higher-order; leading to an enhancement in spatial-resolution. In this paper, the authors analyze certain sound-scenes that were especially challenging for the previously proposed HO-DirAC framework, which the authors postulate could be attributed to the lower-order reconstruction of diffuse sound-field components. Three optimizations for HO-DirAC are proposed, which all employ optimal adaptive mixing and/or energy matching of Ambisonic components based on spatial covariance matrices. The methods are formulated such that they are applied directly in the reconstruction of HOA from the spatially discrete transport audio signals. Notably, a dedicated low-complexity solution without additional side-information is derived. Instrumental evaluations confirm a reduced reconstruction error when using either of the proposed optimizations. These improvements were also demonstrated via a perceptual evaluation, whereby four, six, and twelve transport channels were used to reconstruct (and upmix to) fifth-order reference sound-scenes. The evaluation highlighted the high perceptual performance of the proposed optimizations, including the low-complexity version, thereby improving parametric spatial audio coding and reproduction.