Tracking the “odd”: Meter inference in a culturally diverse music corpus
2014 (English)In: Proceedings of ISMIR - International Conference on Music Information Retrieval, ISMIR , 2014, 425-430 p.Conference paper (Refereed)
In this paper, we approach the tasks of beat tracking, downbeat recognition and rhythmic style classification in nonWestern 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.
Place, publisher, year, edition, pages
ISMIR , 2014. 425-430 p.
Beat Tracking, Meter Inference, Indian music, Turkish music, dynamic Bayesian networks
Research subject Computer Science; Media Technology; Speech and Music Communication
IdentifiersURN: urn:nbn:se:kth:diva-193757OAI: oai:DiVA.org:kth-193757DiVA: diva2:1040416
ISMIR - International Conference on Music Information Retrieval
QC 201610312016-10-272016-10-102016-11-11Bibliographically approved