Music and Audio Computing Lab

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Symbolic Music Similarity and Plagiarism

Determining music plagiarism and music copyright infringement has always been controversial; there are no absolutely quantified metrics that measure the similarity between two songs. In this topic, we explore the relationship between computational similarity and perception of similarity. By comparing similarities from different measures using audio, symbolic and human data, we investigate how several musical elements affect musical plagiarism judgment.


  • A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity
    Saebyul Park, Jongpil Lee, Taegyun Kwon, Jeounghoon Kim, and Juhan Nam
    Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [pdf]
  • SMPD: Symbolic Music Plagiarism Dataset
    Saebyul Park, Halla Kim, Juyong Park, Jeounghoon Kim, Juhan Nam
    The Seventh Seminar on Cognitively Based Music Informatics Research (CogMIR), 2019
  • Comparison of Tonality Models in Measuring Chord Sequence Similarity
    Saebyul Park, Jeounghoon Kim and Juhan Nam
    Proceedings of the 14th International Conference on Music Perception and Cognition (ICMPC), 2016 [pdf]
  • Melodic and Harmonic Similarity for Music Plagiarism: Comparison between computational analysis and perceptual evaluation (abstract)
    Saebyul Park, Seunghun Kim, Dasaem Jeong, Juhan Nam and Jeounghoon Kim
    Proceedings of the Society for Music Perception and Cognition (SMPC), 2015


Saebyul Park, Jongpil Lee, Taegyun Kwon and Juhan Nam