Tracking the "odd": meter inference in a culturally diverse music corpus

TitleTracking the "odd": meter inference in a culturally diverse music corpus
Publication TypeConference Paper
Year of Publication2014
Conference Name15th International Society for Music Information Retrieval (ISMIR) Conference
AuthorsHolzapfel, A., Krebs F., & Srinivasamurthy A.
Pagination425-430
Conference Start Date27/10/2014
Conference LocationTaipei, Taiwan
AbstractIn this paper, we approach the tasks of beat tracking, downbeat recognition and rhythmic style classification in non-Western music. Our approach is based on a Bayesian model, which infers tempo, downbeats and rhythmic style, from an audio signal. The model can be automatically adapted to rhythmic styles and time signatures. For evaluation, we compiled and annotated a music corpus consisting of eight rhythmic styles from three cultures, containing a variety of meter types. We demonstrate that by adapting the model to specific styles, we can track beats and downbeats in odd meter types like 9/8 or 7/8 with an accuracy significantly improved over the state of the art. Even if the rhythmic style is not known in advance, a unified model is able to recognize the meter and track the beat with comparable results, providing a novel method for inferring the metrical structure in culturally diverse datasets.
Published documenthttp://mtg.upf.edu/system/files/publications/Holzapfel_TrackingTheOdd_0.pdf
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