Automated Motivic Analysis: An Exhaustive Approach Based on Closed and Cyclic Pattern Mining in Multidimensional Parametric Spaces

Olivier Lartillot

Research output: Contribution to book/anthology/report/conference proceedingBook chapterResearchpeer-review

3 Citations (Scopus)


Motivic analysis provides very detailed understanding of musical composi- tions, but is also particularly difficult to formalize and systematize. A computational automation of the discovery of motivic patterns cannot be reduced to a mere extraction of all possible sequences of descriptions. The systematic approach inexorably leads to a proliferation of redundant structures that needs to be addressed properly. Global filtering techniques cause a drastic elimination of interesting structures that damages the quality of the analysis. On the other hand, a selection of closed patterns allows for lossless compression. The structural complexity resulting from successive repetitions of patterns can be controlled through a simple modelling of cycles. Generally, motivic patterns cannot always be defined solely as sequences of descriptions in a fixed set of dimensions: throughout the descriptions of the successive notes and intervals, various sets of musical parameters may be invoked. In this chapter, a method is presented that allows for these heterogeneous patterns to be discovered. Motivic repetition with local ornamentation is detected by reconstructing, on top of “surface-level” monodic voices, longer-term relations between non-adjacent notes related to deeper structures, and by tracking motives on the resulting syntagmatic network. These principles are integrated into a computational framework, the MiningSuite, developed in Matlab.
Original languageEnglish
Title of host publicationComputational Music Analysis
EditorsDavid Meredith
Number of pages30
VolumePart V
Place of PublicationCham, Switzerland
Publication date2016
ISBN (Print)978-3-319-25929-1
ISBN (Electronic)978-3-319-25931-4
Publication statusPublished - 2016


  • motivic analysis
  • pattern mining
  • closed pattern
  • cyclic pattern


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