posted on 1996-11-01, 00:00authored byNing Hu, Roger B Dannenberg, Ann L Lewis
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.