Improving Tempo-sensitive and Tempo-robust Descriptors for Rhythmic Similarity

For the description of rhythmic content of music signals usually features are preferred that are invariant in presence of tempo changes. In this paper it is shown that the importance of tempo depends on the musical context. For popular music, a tempo-sensitive feature is improved on multiple datasets using analysis of variance, and it is shown that also a tempo-robust description profits from the integration into the resulting processing framework. Important insights are given into optimal parameters for rhythm description, and limitations of current approaches are indicated.