A Markov-chain Monte-Carlo approach to musical audio segmentation

被引:0
|
作者
Rhodes, Christophe [1 ]
Casey, Michael [1 ]
Abdallah, Samer [1 ]
Sandler, Mark [1 ]
机构
[1] Univ London Goldsmiths Coll, London SE14 6NW, England
关键词
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
This paper describes a method for automatically segmenting and labelling sections in recordings of musical audio. We incorporate the user's expectations for segment duration as an explicit prior probability distribution in a Bayesian framework, and demonstrate experimentally that this method can produce accurate labelled segmentations for popular music.
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页码:5655 / 5658
页数:4
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