Auditory Spectrum-Based Pitched Instrument Onset Detection

E Benetos, Y Stylianou
2010 IEEE Transactions on Audio, Speech, and Language Processing  
In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well as pitchbased features. These features are often combined for maximizing detection performance. Here, the spectral flux and phase slope features
more » ... are derived in the auditory framework and a novel fundamental frequency estimation algorithm based on auditory spectra is introduced. An onset detection algorithm is proposed, which processes and combines the aforementioned features at the decision level. Experiments are conducted on a dataset covering 11 pitched instrument types, consisting of 1829 onsets in total. Results indicate that auditory representations outperform various state-of-the-art approaches, with the onset detection algorithm reaching an F-measure of 82.6%.
doi:10.1109/tasl.2010.2040785 fatcat:ycesxbueafearknnis2anot2eq