  A common defect found when reproducing old vinyl and gramophone recordings
with mechanical devices are the long pulses with significant low-frequency
content caused by the interaction of the arm-needle system with deep scratches
or even breakages on the media surface. Previous approaches to their
suppression on digital counterparts of the recordings depend on a prior
estimation of the pulse location, usually performed via heuristic methods. This
paper proposes a novel Bayesian approach capable of jointly estimating the
pulse location; interpolating the almost annihilated signal underlying the
strong discontinuity that initiates the pulse; and also estimating the long
pulse tail by a simple Gaussian Process, allowing its suppression from the
corrupted signal. The posterior distribution for the model parameters as well
for the pulse is explored via Markov-Chain Monte Carlo (MCMC) algorithms.
Controlled experiments indicate that the proposed method, while requiring
significantly less user intervention, achieves perceptual results similar to
those of previous approaches and performs well when dealing with naturally
degraded signals.
