Backward adaptive prediction: high-order predictors and formant-pitch configurations

An analysis and simulation results are presented comparing the performance of several types of high-order backward adaptive predictors with orders up to 100. Issues in high-order linear predictive coding (LPC) analysis, such as analysis methods, windowing, ill-conditioning, quantization noise effects, and computational complexity, are studied. The performance of the various analysis methods is compared with the conventional sequential formant-pitch predictor. The auto-correlation method (50th order) shows performance advantages over the sequential formant-pitch configurations. Several new backward high-order methods using covariance analysis and a lattice formulation show much better prediction gains than the auto-correlation method