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基于常量Q变换的音符起始点检测 被引量：2

Note Onset Detection Based on Constant Q Transform
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摘要 针对音乐的音阶频率按指数规律分布的特点,提出基于常量Q变换(CQT)的音符起始点检测算法。该算法根据十二平均律的音阶频率分布规律,对音乐信号进行分解,得到一个分音矩阵,利用该分音矩阵生成检测函数,并提取峰值,得到音符起始点向量。实验结果显示,该算法的检测结果要优于2011年MIREX的结果。 The frequencies of music scales are exponentially distributed. This paper proposes an algorithm for note onset detection, which is based on Constant Q Transform（CQT） and adapts to the characteristics of music scales. The music signals are decomposed to a partial, matrix through CQT, according to the frequencies distribution of twelve-tone equal temperament. Detection function is generated using the partial matrix. Peaks are picked, and note onset vector is obtained. Experimental results show that the results are superior to those of 2011 MIREX.
作者 桂文明 刘睿凡 邵曦 白光一
机构地区 南京理工大学计算机科学与技术学院 南京财经大学 南京邮电大学 方舟信息技术(苏州)有限公司
出处 《计算机工程》 CAS CSCD 2013年第10期283-286,共4页 Computer Engineering
基金 国家自然科学基金资助项目"基于内容的流行音乐结构分析的研究"(60902065)
关键词 音符起始点检测 十二平均律 常量Q变换 短时傅里叶变换 分音矩阵 峰值提取 note onset detection twelve-tone equal temperament Constant Q Transform（CQT） Short Time Fourier Transform（STFT） partial matrix peak picking
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献12

  • 1Casey M A, Veltkamp R, Goto M, et al. Content-based Music Information Retrieval: Current Directions and Future Challenges[J]. Proceedings of the IEEE, 2008, 96(4): 668-696.
  • 2Shao Xi. Contend-based Music Classification Summarization and Retrieval[D]. Singapore: National University of Singapore, 2006.
  • 3Goto M. An Audio-based Real-time Beat Tracking System for Music with or Without Drum-sounds[J]. Journal of New Music Research, 2001, 30(2): 159-171.
  • 4陈哲,许洁萍.基于内容的音乐节拍跟踪[J].电子学报,2009,37(B04):156-160. 被引量：5
  • 5Bello J P, Daudet L, Abdallah S, et al. A Tutorial on Onset Detection in Music Signals[J]. IEEE Transactions on Speech and Audio Processing, 2005, 13(5): 1035-1047.
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  • 8Tan Huili, Zhu Yongwei, Chaisorn L, et al. Audio Onset Detection Using Energy-based and Pitch-based Processing[C]// Procl of International Symposium on Circuits and Systems. [S. 1.]: IEEE Press, 2010: 3689-3692.
  • 9桂文明,邵曦,刘睿凡.一种新型音符起始点检测算法[J].计算机工程与应用,2011,47(24):9-11. 被引量：3
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二级参考文献14

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  • 10Shao Xi.Content-based music classification summarization and retrieval[D].Singapore:National University of Singapore,2006.

共引文献5

同被引文献12

  • 1Michael A, Casey RV. Content-based music information retrieval: Current directions and future challenges [ J ]. Proceedings of the IEEE, 2008, 96 (4): 668-696.
  • 2Toh CC, Zhang B, Wang Y. Multiple-feature fusion based on- set detection for solo singing voice [C] //9th ISMIR, 2008.
  • 3Zhou R, Mattavdli M, Zoia G. Music onset detection based on re- sonator time frequency image [J]. IEEE Transactions on Audio, Speech, and Lan__geProcessing, 2008, 16 (8): 1685-1695.
  • 4Schorkhuber, Christian, Anssi Klapuri. Constant-Q transform toolbox for music processing [C] //7th Sound and Music Com- puting Conference, 2010.
  • 5Muller M, Ewert S. Towards timbre-invariant audio features for harmony-based music [J]. IEEE Transactions on Audio, Speech, and Language Processing, 2010, 18 (3):649-662.
  • 6Emiya V, Badeau R, David I3. Multipitch estimation of piano sounds using a new probabilistic spectral smoothness principle [J]. IEEE Transactions on Audio, Speech, and Language Processing, 2010, 18 (6).- 1643-1654.
  • 7MIREX [R/OL]. http://www, music-ir, org/mirex/wiki/MIREX _HOME, 2014.
  • 8Onset Detection Database[DB/OL]. http://grfia, dlsi. ua. es/ cm/proj ects/prosemus/database, php,2014.
  • 9王跃,谢磊,杨玉莲.基于自适应白化的音乐节拍实时跟踪算法[J].计算机应用研究,2009,26(5):1676-1678. 被引量：1
  • 10宋黎明,李明,颜永红.谐波显著度的基频提取方法[J].声学学报,2015,40(2):294-299. 被引量：5

引证文献2

二级引证文献3

计算机工程
2013年 第10期

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