Unsupervised Detection of Music Boundaries by Time Series Structure Features

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Summary

This paper proposes an unsupervised method for boundary detection, combining three basic principles: novelty, homogeneity, and repetition, which is applicable to a wide range of time series beyond the music and audio domains.

Type
article
Published
2012-07-22
Cited by
80
References
28
Access
Open access

Keywords

Computer science, Novelty detection, Novelty, Series (stratigraphy), Benchmark (surveying)

References

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