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基于差分全相位MFCC的音符起点自动检测
引用本文:关欣,李锵,田洪伟.基于差分全相位MFCC的音符起点自动检测[J].计算机工程,2010,36(11):25-26,29.
作者姓名:关欣  李锵  田洪伟
作者单位:天津大学电子信息工程学院,天津,300072
基金项目:国家自然科学基金资助项目(60802049)
摘    要:针对现有的音符起点自动检测方法难以适用于多类音乐信号,计算复杂度较高等问题,提出一种基于差分全相位MFCC的检测算法。通过全相位预处理减小频谱泄露引起的频谱模糊,差分Mel频率倒谱考虑人耳对音乐不同频率响应的非线性特性和音乐信号的动态音乐特征。实验结果表明,与公认综合检测效果好的HFC和ICA等方法相比,该方法计算复杂度小,适用音乐信号类型广,具有更优的综合检测性能。

关 键 词:音符起点检测  Mel频率倒谱系数  全相位预处理  音乐信息检索

Note Onset Automatic Detection Based on Differential All Phase MFCC
GUAN Xin,LI Qiang,TIAN Hong-wei.Note Onset Automatic Detection Based on Differential All Phase MFCC[J].Computer Engineering,2010,36(11):25-26,29.
Authors:GUAN Xin  LI Qiang  TIAN Hong-wei
Affiliation:(School of Electronic and Information Engineering, Tianjin University, Tianjin 300072)
Abstract:To reduce the limited range when used to multiple kinds of music signals and high computing complexity of existing note onset automatic detection methods, a note onset detection algorithm based on differential all phase Mel Frequency Cesptrum Coefficients(MFCC) is presented. All phase preprocessing alleviates spectrum ambiguity because of spectrum leakage. And differential Mel frequency cesptrum considered nonlinearity of human ear when responding to different frequencies and dynamic property of music signal. Experimental result demonstrates this algorithm is fit for multiple kinds of music and has perfect general detection performance with lower computing complexity compared with those of High Frequency Content(HFC) and Independent Component Analysis(ICA).
Keywords:note onset detection  Mel Frequency Cesptrum Coefficients(MFCC)  all phase preprocessing  Music Information Retrieval(MIR)
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