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

Title Tracking the "odd": meter inference in a culturally diverse music corpus
Publication Type Conference Paper
Year of Publication 2014
Conference Name 15th International Society for Music Information Retrieval (ISMIR) Conference
Authors Holzapfel, A. , Krebs F. , & Srinivasamurthy A.
Pagination 425-430
Conference Start Date 27/10/2014
Conference Location Taipei, Taiwan
Abstract In 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.
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