Music Onset Detection Based on Resonator Time Frequency Image Export

@article{citeulike:4537096, abstract = {This paper describes a new method for music onset detection. The novelty of the approach consists mainly of two elements: the time-frequency processing and the detection stages. The resonator time frequency image (RTFI) is the basic time-frequency analysis tool. The time-frequency processing part is in charge of transforming the RTFI energy spectrum into more natural energy- change and pitch-change cues that are then used as input elements for the detection of music onsets by detection tools. Two detection algorithms have been developed: an energy-based algorithm and a pitch-based one. The energy-based detection algorithm exploits energy-change cues and performs particularly well for the detection of hard onsets. The pitch-based algorithm successfully exploits stable pitch cues for the onset detection in polyphonic music, and achieves much better performances than the energy-based algorithm when applied to the detection of soft onsets. Results for both the energy-based and pitch-based detection algorithms have been obtained on a large music dataset.}, author = {Zhou, Ruohua and Mattavelli, M. and Zoia, G.}, booktitle = {Audio, Speech, and Language Processing, IEEE Transactions on}, citeulike-article-id = {4537096}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TASL.2008.2002042}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4618396}, doi = {10.1109/TASL.2008.2002042}, journal = {Audio, Speech, and Language Processing, IEEE Transactions on}, keywords = {onset, onset-detection}, number = {8}, pages = {1685--1695}, posted-at = {2009-05-18 10:22:08}, priority = {2}, title = {Music Onset Detection Based on Resonator Time Frequency Image}, url = {http://dx.doi.org/10.1109/TASL.2008.2002042}, volume = {16}, year = {2008} }

TY - JOUR ID - citeulike:4537096 L3 - citeulike-article-id:4537096 N2 - This paper describes a new method for music onset detection. The novelty of the approach consists mainly of two elements: the time-frequency processing and the detection stages. The resonator time frequency image (RTFI) is the basic time-frequency analysis tool. The time-frequency processing part is in charge of transforming the RTFI energy spectrum into more natural energy- change and pitch-change cues that are then used as input elements for the detection of music onsets by detection tools. Two detection algorithms have been developed: an energy-based algorithm and a pitch-based one. The energy-based detection algorithm exploits energy-change cues and performs particularly well for the detection of hard onsets. The pitch-based algorithm successfully exploits stable pitch cues for the onset detection in polyphonic music, and achieves much better performances than the energy-based algorithm when applied to the detection of soft onsets. Results for both the energy-based and pitch-based detection algorithms have been obtained on a large music dataset. IS - 8 JF - Audio, Speech, and Language Processing, IEEE Transactions on EP - 1695 TI - Music Onset Detection Based on Resonator Time Frequency Image VL - 16 T2 - Audio, Speech, and Language Processing, IEEE Transactions on SP - 1685 KW - onset KW - onset-detection AU - Zhou, Ruohua AU - Mattavelli, M AU - Zoia, G PY - 2008/// UR - http://dx.doi.org/10.1109/TASL.2008.2002042 ER -