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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hui Li Tan Yongwei Zhu Chaisorn, L. Rahardja, S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Institute for Infocomm Research, A∗STAR (Hui Li Tan; Yongwei Zhu; Chaisorn, L.; Rahardja, S.) |
| 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. |
| Starting Page | 3689 |
| Ending Page | 3692 |
| File Size | 232585 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424453085 |
| DOI | 10.1109/ISCAS.2010.5537762 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-05-30 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Phase detection Instruments Frequency Robustness Music Detectors Face detection Timbre Feature extraction Machine learning |
| Content Type | Text |
| Resource Type | Article |
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