|Title||Maximum Filter Vibrato Suppression for Onset Detection|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Böck, S, Widmer, G|
|Conference Name||Proceedings of the 16th International Conference on Digital Audio Effects (DAFx-13)|
|Conference Location||Maynooth, Ireland|
|Keywords||maximum filter, onset detection, vibrato suppression|
We present SuperFlux - a new onset detection algorithm with vibrato suppression. It is an enhanced version of the universal spectral flux onset detection algorithm, and reduces the number of false positive detections considerably by tracking spectral trajectories with a maximum filter. Especially for music with heavy use of vibrato (e.g., sung operas or string performances), the number of false positive detections can be reduced by up to 60% without missing any additional events. Algorithm performance was evaluated and compared to state-of-the-art methods on the basis of three different datasets comprising mixed audio material (25,927 onsets), violin recordings (7,677 onsets) and operatic solo voice recordings (1,448 onsets). Due to its causal nature, the algorithm is applicable in both offline and online real-time scenarios.