In this paper experiments done towards improving the performance of systems retrieving musical rhythm axe described. Authors briefly review machine learning models used to estimate tendency of sounds to be located in accented positions. This is done on the basis of their physical attributes such as duration, frequency and amplitude. For this purpose Data Mining association rule model and neural networks with discrete output - LVQ networks are used. By means of evaluation method introduced by the authors it is possible to compare the results returned by both models. This work aims at retrieving multi-level rhythmic structure of a musical piece on the basis of its melody, which may result in systems retrieval systems for automatic music identification.
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