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ICASSP
2009
IEEE

Joint estimation of short-term and long-term predictors in speech coders

10 years 1 months ago
Joint estimation of short-term and long-term predictors in speech coders
In low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a shortterm and a long-term linear predictor. These two predictors are usually found in a sequential and therefore suboptimal approach. In this paper we propose an analysis model that jointly finds the two predictors by adding a regularization term in the minimization process to impose sparsity constraints on a high order predictor. The result is a linear predictor that can be easily factorized into the short-term and long-term predictors. This estimation method is then incorporated into an Algebraic Code Excited Linear Prediction scheme and shows to have a better performance than traditional cascade methods and other joint optimization methods, offering lower distortion and higher perceptual speech quality.
Daniele Giacobello, Mads Græsbøll Chr
Added 17 Aug 2010
Updated 17 Aug 2010
Type Conference
Year 2009
Where ICASSP
Authors Daniele Giacobello, Mads Græsbøll Christensen, Joachim Dahl, Søren Holdt Jensen, Marc Moonen
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