Design and performance of trellis vector quantizers for speech signals

In this paper, we present design algorithms for linear predictive vector quantizers with trellis structures that when combined with appropriate search procedures can achieve lower distortions than conventional memoryless vector quantizers. We consider two types of trellis structures: shift register and minimum degradation network. In the shift register case (SR-TVQ), the state of the trellis encoder corresponds to the contents of the shift register; it therefore does not require an explicit state transition matrix. The minimum degradation network is a state transition matrix obtained through a pruning procedure (P-TVQ) to give minimum distortion degradation from an omni search (full rate) vector quantizer. The role of search procedure, the delay requirements of each type of the encoders, the performance of the designs, and a comparison of the two methods are discussed.