Interpolation of Missing Samples in Sound Signals Based on Autoregressive Modeling
Laurent Oudre
→ BibTeX
@article{ipol.2018.23,
    title   = {{Interpolation of Missing Samples in Sound Signals Based on Autoregressive Modeling}},
    author  = {Oudre, Laurent},
    journal = {{Image Processing On Line}},
    volume  = {8},
    pages   = {329--344},
    year    = {2018},
    doi     = {10.5201/ipol.2018.23},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2018.23}}
published
2018-10-17
reference
Laurent Oudre, Interpolation of Missing Samples in Sound Signals Based on Autoregressive Modeling, Image Processing On Line, 8 (2018), pp. 329–344. https://doi.org/10.5201/ipol.2018.23

Communicated by Gaël Richard, Rafael Grompone von Gioi
Demo edited by Miguel Colom

Abstract

This article proposes an implementation and a study of the paper 'Adaptive Interpolation of Discrete-Time Signals That Can Be Modeled as Autoregressive Processes' by Janssen et al. The algorithm presented in this paper allows one to reconstruct an audio signal which presents localized degradations by interpolating the missing samples. This method assumes that the signal can locally be modeled as a realization of an autoregressive process and iteratively estimates the model parameters and the interpolated samples by minimizing a quadratic criterion. We investigate the limits and the algorithmic aspects of this method on several audio examples.

Download