4th International Conference on Spoken Language Processing

Philadelphia, PA, USA
October 3-6, 1996

Continuous Adaptation of Linear Models with Impulsive Excitation

Steve W. Beet, L. Baghai-Ravary

Department of Electronic and Electrical Engineering, University of Sheffield, UK

This paper presents a new approach to continuously-adaptive system modelling, designed for the analysis of autoregressive (AR) systems excited by signals including an impulsive component. Voiced speech is well represented by such a model, and is used to demonstrate the advantages of the new- approach These include: 1. AR model parameter estimates are more stable in the region of pitch events. 2. A faster adaptation rate can be used, reducing the recovery time after plosives or other sudden changes in signal statistics. The new method is based on multiple simultaneous estimates of each sample, using separate but related estimators. The general concept is illustrated here using a linear prediction (LP) approach to continuously-adaptive autoregressive (AR) modelling, based on the least mean square (LMS) algorithm.

Full Paper

Bibliographic reference.  Beet, Steve W. / Baghai-Ravary, L. (1996): "Continuous adaptation of linear models with impulsive excitation", In ICSLP-1996, 2250-2253.