A Bayesian approach to the detection and correction of error bursts in audio signals

The a posteriori probability for the location of bursts of noise additively superimposed on a Gaussian autoregressive (AR) process is derived. The maximum a posteriori (MAP) solution for noise burst position is obtained by using a simple search procedure, yielding the noise burst location corresponding to minimum probability of error. This procedure finds application in digital audio processing, where clicks and scratches may be modeled as additive bursts of noise. The method permits accurate detection of these degradations and their subsequent replacement (interpolation). Experiments were carried out on both real audio data and synthetic AR processes, and comparisons are made with previous techniques