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Conference papers
Enhancing downbeat detection when facing different music styles
Abstract : This paper focuses on the automatic rhythm analysis of musical audio at the bar level. We propose a novel approach for robust downbeat detection. It uses well-chosen complementary features, inspired by musical considerations. In particular, a note accentuation model and a detection of pattern changes are introduced. We estimate the time signature by examining the similarity of frames at the beat level. The features are selected through a linear SVM model or a weighted sum. The whole system is evaluated on five different datasets of various musical styles and shows improvement over the state of the art.
https://hal.telecom-paris.fr/hal-02286904
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 4:20:55 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:53 PM
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 4:20:55 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:53 PM
