Hockman, J.A., Davies, M.E.P., Fujinaga, I., 2012.
One in the jungle: Downbeat detection in hardcore, jungle, and drum and bass
Output Type: | Conference paper |
Publication: | Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012 |
Pagination: | pp. 169-174 |
Hardcore, jungle, and drum and bass (HJDB) are fast-paced electronic dance music genres that often employ resequenced breakbeats or drum samples from jazz and funk percussionist solos. We present a style-specific method for downbeat detection specifically designed for HJDB. The presented method combines three forms of metrical information in the prediction of downbeats: low-level onset event information; periodicity information from beat tracking; and high-level information from a regression model trained with classic breakbeats. In an evaluation using 206 HJDB pieces, we demonstrate superior accuracy of our style specific method over four general downbeat detection algorithms. We present this result to motivate the need for style-specific knowledge and techniques for improved downbeat detection. © 2012 International Society for Music Information Retrieval.