Knowledge Commons of Institute of Automation,CAS
Note onset detection based on sparse decomposition | |
Shao, Xi1; Gui, Wenming2; Xu, Changsheng3 | |
发表期刊 | MULTIMEDIA TOOLS AND APPLICATIONS |
2016-03-01 | |
卷号 | 75期号:5页码:2613-2631 |
文章类型 | Article |
摘要 | Music onset detection is significant and essential for obtaining the high-level music features such as rhythm, beat, music paragraph and structure. The traditional methods for onset detection which employ Short Time Fourier Transform (STFT)-based or Wavelet Transform (WT)-based features to characterize music signal generally lack adaptiveness for representing the stationary and non-stationary part of the music signal. This will lead to the degraded performance for music note onset detection. To solve this problem, a new algorithm for note onset detection based on sparse decomposition is proposed. Firstly, the musical signals are sparsely decomposed with Matching Pursuit (MP), and then the hybrid detection algorithm which combines namely the Degree of Explanation (DE) and the Change of Partials (CP) is applied to the sparse representation of the music signal. Finally, a modified peak-picking algorithm is employed to generate onset vectors. The experiments on the dataset with 2050 onsets show that our results are superior to those of MIREX 2013. For the polyphonic music which is the most widely used form in our real life, the proposed algorithm has better performance than the other algorithms. |
关键词 | Note Onset Detection Sparse Decomposition Matching Pursuit |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1007/s11042-015-2656-8 |
关键词[WOS] | MATCHING PURSUIT ; SIGNALS ; MUSIC |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Nature Science Foundation of China(60902065 ; Beijing Natural Science Foundation(4152053) ; 61401227) |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000372027000013 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/11366 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | 1.Nanjing Univ Posts & Telecommun, Coll Commun & Informat Engn, 172,66 Xinmofan Rd, Nanjing 210003, Jiangsu, Peoples R China 2.Jinling Inst Technol, Nanjing 210003, Jiangsu, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Shao, Xi,Gui, Wenming,Xu, Changsheng. Note onset detection based on sparse decomposition[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2016,75(5):2613-2631. |
APA | Shao, Xi,Gui, Wenming,&Xu, Changsheng.(2016).Note onset detection based on sparse decomposition.MULTIMEDIA TOOLS AND APPLICATIONS,75(5),2613-2631. |
MLA | Shao, Xi,et al."Note onset detection based on sparse decomposition".MULTIMEDIA TOOLS AND APPLICATIONS 75.5(2016):2613-2631. |
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