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Paper title: A NEURAL-NETWORK-BASED APPROACH TO SPEECH SIGNAL PREDICTION
Author(s): RUI J.P. DE FIGUEIREDO,
Abstract: In this paper a new approach to speech signal prediction is presented. The approach
deploys an EKF (Extended Kalman Filter)-based learning algorithm for this
application. Simulation results show that the proposed neural network approach leads to
better performance than the well-known linear predictive coding (LPC) approach which
uses the Levinson-Durbin algorithm for predictor design.
Keywords: Neural networks, Linear predictors Year: 2010 | Tome: 55 | Issue: 1 | Pp.: 42-48
Full text : PDF (174 KB) |
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