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Sparse autoregressive modeling

In the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation is given ina factorized form - the model is a cascade of the so-called formant and pitch lters. Thistechnique can be applied successfully in the algorithm for detection and reconstruction ofdistorted archived audio recordings. It is shown that the choice of the PD algorithm has signicant impact on improving the one-step-ahead predictor capabilities based on SAR modelwhich in consequence may improve detection/reconstruction performance of the algorithm.

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Category
Aktywność konferencyjna
Type
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Language
polski
Publication year
2012

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