Abstract:
The GrooveToolbox is a new Python library implementing numerous algorithms, both novel and pre-existing, for the analysis of symbolic drum loops, including rhythm features, similarity metrics and microtiming features. As part of the GrooveToolbox we introduce two new metrics of rhythm similarity and four new features for describing the perceptually salient properties of microtiming deviations in drum loops. Based on a two-part perceptual evaluation, we show these four new microtiming features can each correlate to similarity perception, and be used along with rhythm similarity metrics to improve personalized similarity models for complex drum loops. A new measure of structural rhythmic similarity is also shown to correlate more strongly to similarity perception of drum loops than the more commonly used Hamming distance. These results point to the potential application of the GrooveToolbox and its new features in drum loop analysis for intelligent music production tools. The GrooveToolbox may be found at: https://github.com/fredbru/GrooveToolbox
