Sixth European Conference on Speech Communication and Technology

Budapest, Hungary
September 5-9, 1999

Adaptive Nonlinear Prediction Based on Order Statistics for Speech Signals

Tetsuya Shimamura, Haruko Hayakawa

Department ofInformation and Computer Sciences Saitama University, 255 Shimo-Okubo, Urawa, 338-8570, Japan

This paper proposes a novel adaptive algorithm for nonlinear prediction of speech signals, which turns out to be the adaptation procedure for an order statistic LMS predictor. The LMS-L filter Pitas et al. addressed is modified to preserve the time information in the input vector for the adaptation, in which a coeficient matrix is utilized to update the predictor coeficients. Computer simulations demonstrate that the novel nonlinear predictor provides better performance than the Volterra quadratic predictor as well as the linear predictor.

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Bibliographic reference.  Shimamura, Tetsuya / Hayakawa, Haruko (1999): "Adaptive nonlinear prediction based on order statistics for speech signals", In EUROSPEECH'99, 347-350.