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We present a statistical method for restoring audio signals which have been coarsely quantized without dither. The signal is modeled as a piecewise-stationary linear autoregressive process. Parameter and signal estimation are performed using sampling methods. To improve performance, sinusoidal components are incorporated into the model. Model order estimation and sinusoid selection are found to be crucial to the quality of the restoration.
Author (s): Troughton, Paul T.;
Godsill, Simon J.;
Affiliation:
University of Cambridge, Cambridge, UK
(See document for exact affiliation information.)
AES Convention: 107
Paper Number:5055
Publication Date:
1999-09-06
Session subject:
Digital Signal Processing
DOI:
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Troughton, Paul T.; Godsill, Simon J.; 1999; Restoration of Coarsely Quantized Audio Signals Using Markov Chain Monte Carlo Methods [PDF]; University of Cambridge, Cambridge, UK; Paper 5055; Available from: https://aes.org/publications/elibrary-page/?id=8125
Troughton, Paul T.; Godsill, Simon J.; Restoration of Coarsely Quantized Audio Signals Using Markov Chain Monte Carlo Methods [PDF]; University of Cambridge, Cambridge, UK; Paper 5055; 1999 Available: https://aes.org/publications/elibrary-page/?id=8125
@inproceedings{Troughton1999restoration,
title={{Restoration of Coarsely Quantized Audio Signals Using Markov Chain Monte Carlo Methods}},
author={Troughton, Paul T. and Godsill, Simon J.},
year={1999},
month={sep},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 5055; AES Convention 107; September 1999},
number={5055},
organization={AES},
}
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