We introduce a representation for rhythmic patterns that is insensitive to minor tempo deviations and that has well-defined behavior for larger changes in tempo. We have combined the representation with an Euclidean distance measure and compared it to other systems in a classification task of ballroom music. Compared to the other systems, the proposed representation shows much better generalization behavior when we limit the training data to songs with different tempi than the query. When both test and training data contain songs with similar tempo, the proposed representation has comparable performance to other systems.
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