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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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