A probabilistic model of melodic similarity

  • Hu N
  • Dannenberg R
  • Lewis A
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Abstract

Melodic similarity is an important concept for music databases, musicological studies, and interactive music systems. Dynamic programming is commonly used to compare melodies, often with a distance function based on pitch differences measured in semitones. This approach computes an “edit distance” as a measure of melodic dissimilarity. The problem can also be viewed in probabilistic terms: What is the probability that a melody is a “mutation” of another melody, given a table of mutation probabilities? We explain this approach and demonstrate how it can be used to search a database of melodies. Our experiments show that the probabilistic model performs better than a typical “edit distance” comparison. 1

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Authors

  • Ning Hu

  • Roger B. Dannenberg

  • Ann L. Lewis

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