Abstract:

A two-stage algorithm for removing noise from recorded music signals (first proposed in Berger et al., ICMC, 1995) is described and updated. The first stage selects the ``best'' local trigonometric basis for the signal and models noise as the part having high entropy [see Berger et al., J. Audio Eng. Soc. 42(10), 808--818 (1994)]. In the second stage, the original source and the model of the noise obtained from the first stage are expanded into dyadic trees of smooth local sine bases. The best basis for the source signal is extracted using a relative entropy function (the Kullback--Leibler distance) to compare the sum of the costs of the children nodes to the cost of their parent node; energies of the noise in corresponding nodes of the model noise tree are used as weights. The talk will include audio examples of various stages of the method and proposals for further research.