Speech Spectral Quantizers for Wideband Speech Coding

Abstract. In this treatise a range of Line Spectrum Frequency (LSF) Vector Quantization (VQ) schemes were studied comparatively, which were designed for wideband speech codecs. Both predictive arrangements and memoryless schemes were investigated. Specifically, both memoryless Split Vector Quantization (SVQ) and Classified Vector Quantization (CVQ) were studied. These techniques exhibit a low complexity and high channel error resilience, but require high bit rates for maintaining high speech quality. By contrast, Predictive Vector Quantizers (PVQ) offer an enhanced Spectral Distortion (SD) performance, although they are sensitive to channel error propagation. It is shown that the family of so-called Safety-Net Vector Quantization (SNVQ) schemes offers a good design compromise, providing an extension to memory-based PVQ, and thereby improving the performances both over noisy and noiseless channels