Measuring structural similarity in music

Research output: Contribution to journalArticlepeer-review


This paper presents a novel method for measuring the structural similarity between music recordings. It uses recurrence plot analysis to characterize patterns of repetition in the feature sequence, and the normalized compression distance, a practical approximation of the joint Kolmogorov complexity, to measure the pairwise similarity between the plots. By measuring the distance between intermediate representations of signal structure, the proposed method departs from common approaches to music structure analysis which assume a block-based model of music, and thus concentrate on segmenting and clustering sections. The approach ensures that global structure is consistently and robustly characterized in the presence of tempo, instrumentation, and key changes, while the used metric provides a simple to compute, versatile and robust alternative to common approaches in music similarity research. Finally, experimental results demonstrate success at characterizing similarity, while contributing an optimal parameterization of the proposed approach.

Original languageEnglish (US)
Article number5711645
Pages (from-to)2013-2025
Number of pages13
JournalIEEE Transactions on Audio, Speech and Language Processing
Issue number7
StatePublished - 2011


  • Audio signal processing
  • computer audition
  • music information retrieval (MIR)
  • music structure analysis
  • sound similarity

ASJC Scopus subject areas

  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering


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