Multiple-Description Predictive-Vector Quantization With Applications to Low Bit-Rate Speech Coding Over Networks

An algorithm for designing linear prediction-based two-channel multiple-description predictive-vector quantizers (MD-PVQs) for packet-loss channels is presented. This algorithm iteratively improves the encoder partition, the set of multiple description codebooks, and the linear predictor for a given channel loss probability, based on a training set of source data. The effectiveness of the designs obtained with the given algorithm is demonstrated using a waveform coding example involving a Markov source as well as vector quantization of speech line spectral pairs