Kalman filtering techniques in speech coding

Abstract

The use of Kalman filtering (KF) techniques in speech coding is investigated. The authors show that the common linear predictor (LP) is a special case of the KF based on an all-pole signal model. They also show that the KF algorithm provides fixed-lag smoothing at no additional complexity. Simulation results reveal that KF based speech coding has significant advantage over the equivalent LP based systems, particularly when used with coarsely quantized measurements.<>