Localization of impulsive disturbances in archive audio signals using predictive matched filtering

The problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated with the sequence of multi-step-ahead prediction errors yielded by the model-based signal predictor. It is shown that predictive matched filtering is an efficient and computationally affordable disturbance localization technique - when combined with the classical detection method based on autoregressive modeling, it can significantly improve restoration results.