Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity

@article{Serr2014UnsupervisedMS,
  title={Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity},
  author={Joan Serr{\`a} and Meinard Mueller and Peter Grosche and Josep Llu{\'i}s Arcos},
  journal={IEEE Transactions on Multimedia},
  year={2014},
  volume={16},
  pages={1229-1240}
}
Automatically inferring the structural properties of raw multimedia documents is essential in today's digitized society. Given its hierarchical and multi-faceted organization, musical pieces represent a challenge for current computational systems. In this article, we present a novel approach to music structure annotation based on the combination of structure features with time series similarity. Structure features encapsulate both local and global properties of a time series, and allow us to… CONTINUE READING

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