Restoration of Audio Documents by Means of Extended Kalman Filter

We present some results on audio restoration obtained with an algorithm that solves the problems of broadband noise filtering, signal parameters tracking, and impulsive noise removal by using the Extended Kalman Filter (EKF) theory. We show that, to achieve maximum performance, it is essential to optimize the EKF implementation. To this purpose, having to cope with the nonstationarity of the audio signal, we use two properly combined EKF filters (forward and backward), and introduce a bootstrapping procedure for model tracking. The careful combination of the proposed techniques and an accurate choice of some critical parameters, allows to improve the performance of the EKF algorithm. The presented procedure is validated by listening tests.