Content-based music structure analysis with applications to music semantics understanding
Content-based music structure analysis with applications to music semantics understanding
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DOI：
10.1145/1027527.1027549
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发表时间：
2004-10
期刊：
影响因子：
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通讯作者：
N. Maddage;Changsheng Xu;M. Kankanhalli;Xi Shao
中科院分区：
文献类型：
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作者：
N. Maddage;Changsheng Xu;M. Kankanhalli;Xi Shao
本文提出了一种新的音乐结构分析方法。提出了一种新的分割方法——节拍空间分割，并将其用于音乐和弦检测和声乐/器乐边界检测。和弦模式序列中错误检测的和弦和错误分类的声乐/器乐框架使用来自音乐创作领域知识的启发式方法进行纠正。基于旋律的相似区域通过动态规划匹配子和弦模式来检测。进一步分析基于旋律的相似区域的声乐内容，检测基于内容的相似区域。基于旋律和内容的相似区域，识别音乐结构。实验结果令人鼓舞，表明该方法的性能优于现有的方法。我们相信音乐结构分析可以极大地帮助音乐语义理解，从而帮助音乐转录、总结、检索和流媒体。
In this paper, we present a novel approach for music structure analysis. A new segmentation method, beat space segmentation, is proposed and used for music chord detection and vocal/instrumental boundary detection. The wrongly detected chords in the chord pattern sequence and the misclassified vocal/instrumental frames are corrected using heuristics derived from the domain knowledge of music composition. Melody-based similarity regions are detected by matching sub-chord patterns using dynamic programming. The vocal content of the melody-based similarity regions is further analyzed to detect the content-based similarity regions. Based on melody-based and content-based similarity regions, the music structure is identified. Experimental results are encouraging and indicate that the performance of the proposed approach is superior to that of the existing methods. We believe that music structure analysis can greatly help music semantics understanding which can aid music transcription, summarization, retrieval and streaming.