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This paper introduces an unsupervised model for melodic segmentation that extends a method initially proposed in computational biology. In the model segments are identified as sections of maximal contrast within a musical piece, using for this the Jensen-Shannon divergence. The model is extended upon its original formulation, and experiments to test its performance are carried out for a small set...
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