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Conference Paper

The Matrix profile for motif discovery in audio - an example application in Carnatic music


Pearson,  Lara       
Department of Music, Max Planck Institute for Empirical Aesthetics, Max Planck Society;

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Nuttall, T., Plaja, G., Pearson, L., & Serra, X. (2021). The Matrix profile for motif discovery in audio - an example application in Carnatic music. In T. Kitahara, M. Aramaki, & R. Kronland-Martinet (Eds.), Music in the AI Era: Proceedings of the 15th International Symposium on Computer Music Multidisciplinary Research (pp. 109-118).

Cite as: https://hdl.handle.net/21.11116/0000-000C-1FC3-6
We present here a pipeline for the automated discovery of repeated
motifs in audio. Our approach relies on state-of-the-art source separation, predominant pitch extraction and time series motif detection via the matrix profile.
Owing to the appropriateness of this approach for the task of motif recognition
in the Carnatic musical style of South India, and with access to the recently released Saraga Dataset of Indian Art Music, we provide an example application
on a recording of a performance in the Carnatic raga ¯ , R¯itigaul.a, finding 56 distinct patterns of varying lengths that occur at least 3 times in the recording. The
authors include a discussion of the potential musicological significance of this
motif finding approach in relation to the particular tradition and beyond.