Title :
Audio onset detection using energy-based and pitch-based processing
Author :
Hui Li Tan ; Zhu, Yongwei ; Chaisorn, Lekha ; Rahardja, Susanto
fDate :
May 30 2010-June 2 2010
Abstract :
Leveraging on the strength of energy-based processing for transient detection and pitch-based processing for softer onsets detection, we present a system that combines both energy and pitch cues for detecting onsets from different instrument categories. Given an audio input from an arbitrary instrument category, the system performs preliminary onset categorization based on the general note characteristics and then performs onsets integration based on the categorization. In addition, the proposed pitch processing technique explores musically relevant features extracted from the chromagram, which are robust for detecting pitch changes. The proposed system showed good detection performance on the MIREX audio onset detection dataset.
Keywords :
audio signal processing; feature extraction; signal detection; MIREX audio onset detection dataset; chromagram; energy-based processing; musical instrument; musically relevant feature extraction; pitch-based processing; transient detection; Detectors; Face detection; Feature extraction; Frequency; Instruments; Machine learning; Music; Phase detection; Robustness; Timbre;
Conference_Titel :
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-5308-5
Electronic_ISBN :
978-1-4244-5309-2
DOI :
10.1109/ISCAS.2010.5537762