Unsupervised Discovery of Temporal Structure in Music.
IEEE Journal of Selected Topics in Signal Processing(2011)
摘要
We describe a data-driven algorithm for automatically identifying repeated patterns in music which analyzes a feature matrix using shift-invariant probabilistic latent component analysis. We utilize sparsity constraints to automatically identify the number of patterns and their lengths, parameters that would normally need to be fixed in advance, as well as to control the structure of the decomposi...
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关键词
Probabilistic logic,Signal processing algorithms,Algorithm design and analysis,Matrix decomposition,Hidden Markov models,Feature extraction,Music
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