A Hybrid Approach to Musical Note Onset Detection

Christopher Duxbury; Mark Sandler; Mike Davies
DAFx-2002 - Hamburg
Common problems with current methods of musical note onset detection are detection of fast passages of musical audio, detection of all onsets within a passage with a strong dynamic range and detection of onsets of varying types, such as multi-instrumental music. We present a method that uses a subband decomposition approach to onset detection. An energy-based detector is used on the upper subbands to detect strong transient events. This yields precision in the time resolution of the onsets, but does not detect softer or weaker onsets. A frequency based distance measure is formulated for use with the lower subbands, improving detection accuracy of softer onsets. We also present a method for improving the detection function, by using a smoothed difference metric. Finally, we show that the detection threshold may be set automatically from analysis of the statistics of the detection function, with results comparable in most places to manual setting of thresholds.