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Advances in virtual reality have generated substantial interest in accuratelyreproducing and storing spatial audio in the higher order ambisonics (HOA)representation, given its rendering flexibility. Recent standardization for HOAcompression adopted a framework wherein HOA data are decomposed into principalcomponents that are then encoded by standard audio coding, i.e., frequencydomain quantization and entropy coding to exploit psychoacoustic redundancy. Anoted shortcoming of this approach is the occasional mismatch in principalcomponents across blocks, and the resulting suboptimal transitions in the datafed to the audio coder. Instead, we propose a framework where singular valuedecomposition (SVD) is performed after transformation to the frequency domainvia the modified discrete cosine transform (MDCT). This framework not onlyensures smooth transition across blocks, but also enables frequency dependentSVD for better energy compaction. Moreover, we introduce a novel noisesubstitution technique to compensate for suppressed ambient energy in discardedhigher order ambisonics channels, which significantly enhances the perceptualquality of the reconstructed HOA signal. Objective and subjective evaluationresults provide evidence for the effectiveness of the proposed framework interms of both higher compression gains and better perceptual quality, comparedto existing methods.

Frequency Domain Singular Value Decomposition for Efficient Spatial Audio Coding