Transform Coding of Speech with Pyramid Vector Quantization

The pyramid vector quantizer (PVQ) is a lattice quantizer that was motivated bv the geometric properties of a memoryless Laplacian source. For large rates and the cubic lattice. the PVQ provides improvements of 2.39, 5.64, and 8.40 dB for memoryless Gaussian, Laplacian, and gamma sources, respectivelv, compared to the corresponding optimum (noniuniform) scalar quantizer. The lattice basis of the PVQ allows simple encoding and decoding algorithms with a complexity that grows only linearly with the vector dimension. A correlated source such as speech has a geometric nature that is not well suited to the PVQ unless transform coding is used. It is demonstrated that an encoding system using a cosine transform, interleaving of the transform coefficients, and pyramid vector quantization can achieve signal-to-noise ratio (SNR) performance in excess of 20dB for an average rate of 2 bits/sample.