Determination of the meter of musical audio signals: Seeking recurrences in beat segment descriptors
Determination of the meter of musical audio signals: Seeking recurrences in beat segment descriptors
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音乐音频信号节拍的确定：寻找节拍段描述符中的重复
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
P. Herrera
中科院分区：
文献类型：
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作者：
F. Gouyon;P. Herrera
我们解决了按节拍对复调音乐音频信号进行分类的问题：有规律地重复出现的重音（或重拍）之间的节拍数。这个问题被简化为“双重”/“三重”决策。实验是在70个实例数据库中进行的（20个音乐片段，没有特定的体裁和音色限制）。我们的方法旨在验证一个假设，即重拍的声学证据可以在信号的低水平特征上测量；特别关注它们的时间循环。我们实验了几种方法来解决特征选择问题，并报告了一些有趣的结果：对非常小的一组温度描述符（即4）的测量和随后的处理（基于自相关函数）允许达到大约95%的正确分类。仅使用时间质心，几乎可以达到90%的正确率。
We address the problem of classifying polyphonic musical audio signals by their meter: the number of beats between regularly recurring accents (or downbeats). The problem is simplified to a ‘duple ’/‘triple’ decision. Experiments have been conducted on a 70 instances database (20s excerpts from pieces of music without particular genre nor timbre restriction). Our approach aims to test the hypothesis that acoustic evidences for downbeats can be measured on signal low-level features; focusing especially on their temporal recurrences. We experimented several approaches to the problem of feature selection and report some interesting results: measurements of a very small set of beat descriptors (i.e. 4) and subsequent processing (based on autocorrelation functions) permit to reach around 95% of correct classification. Using only the temporal centroid, almost 90% of correct classification can be achieved.