Rate-distortion modeling of spherical vector quantization performance in transform excitation audio coding

A block-based Gaussian mixture model (GMM) is used to model the distribution of the transform audio data encoded using spherical vector quantization and lossless coding. The expectation-maximization algorithm is used to design the GMM to model the marginal density of the transform coefficients and the block energy density. A GMM-based rate-distortion function is derived and shown to closely match the observed spherical VQ performance.