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Abstract
Large digital archives of ethnic music require automatic tools to provide musical content descriptions. While various automatic approaches are available, they are to a wide extent developed for Western popular music. This paper aims to analyse how automated tempo estimation approaches perform in the context of Central-African music. To this end we collect human beat annotations for a set of musical fragments, and compare them with automatic beat tracking sequences. We first analyse the tempo estimations derived from annotations and beat tracking results. Then we examine an approach, based on mutual agreement between automatic and human annotations, to automate such analysis, which can serve to detect musical fragments with high tempo ambiguity.
Acknowledgments
This research was supported by the University College Ghent and by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583).
We are grateful to the RMCA (Royal Museum for Central Africa) in Belgium for providing access to its unique archive of Central African music.
Finally we would like to thank José R. Zapata for his support in running beat tracking algorithms.
Notes
Olmo Cornelis, University College Ghent, School of Arts, Hoogpoort 64, 9000 Ghent, Belgium.
British Library (London), CREM and SDM (Paris), Ethnologisches Museum (Berlin), RMCA (Brussels), Essen Folksong Collection (Warsaw), GTF (Vienna), and many more.
See Appendix C for a number references to digitization projects.
The Music Information Retrieval Evaluation eXchange (MIREX) is an annual evaluation campaign for Music Information Retrieval (MIR) algorithms. More info about MIREX can be found on http://www.music-ir.org.