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1st International Workshop on Reading Music Systems


Paris, September 20

PRAIg '18 / +pics


11th international workshop on Machine Learning and Music


Stockholm: 13-15th July 2018



  1. Bernabeu, J.F., Calera-Rubio, J., Iñesta, J.M., Rizo, D.
    "A probabilistic approach to melodic similarity"
    Proceedings of MML 2009, pp. 48-53 (2009)
    : bibtex : pdf : Workshop URL

    Melodic similarity is an important research topic in music information retrieval. The representation of symbolic music by means of trees has proven to be suitable in melodic similarity computation, because they are able to code rhythm in their structure leaving only pitch representations as a degree of freedom for coding. In order to compare trees, different edit distances have been previously used. In this paper, stochastic k-testable tree-models, formerly used in other domains like structured document compression or natural language processing, have been used for computing a similarity measure between melody trees as a probability and their performance has been compared to a classical tree edit distance.

@inproceedings {
 author = "Bernabeu, J.F., Calera-Rubio, J., Iñesta, J.M., Rizo, D.",
 title  = "A probabilistic approach to melodic similarity",
 booktitle = "Proceedings of MML 2009",
 pages = "48-53",
 year = "2009"
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