Melodic Similarity: Looking for a Good Abstraction Level. Grachten, M., Arcos, J. L., & Mántaras, R. L. D. In Proceedings of the 5th International Society for Music Information Retrieval, 2004. abstract bibtex Computing melodic similarity is a very general problem with diverse musical applications ranging from music analysis to content-based retrieval. Choosing the appropriate level of representation is a crucial issue and depends on the type of application. Our research interest concerns the development of a CBR system for expressive music processing. In that context, a well chosen distance measure for melodies is a crucial issue. In this paper we propose a new melodic similarity measure based on the I/R model for melodic structure and compare it with other existing measures. The experimentation shows that the proposed measure provides a good compromise between discriminatory power and ability to recognize phrases from the same song.
@inproceedings{grachten.ea2004-melodic,
abstract = {Computing melodic similarity is a very general
problem with diverse musical applications ranging
from music analysis to content-based
retrieval. Choosing the appropriate level of
representation is a crucial issue and depends on the
type of application. Our research interest concerns
the development of a CBR system for expressive music
processing. In that context, a well chosen distance
measure for melodies is a crucial issue. In this
paper we propose a new melodic similarity measure
based on the I/R model for melodic structure and
compare it with other existing measures. The
experimentation shows that the proposed measure
provides a good compromise between discriminatory
power and ability to recognize phrases from the same
song.},
author = {Grachten, Maarten and Arcos, Josep Lluis and
M{\'{a}}ntaras, Ramon L{\'{o}}pez De},
booktitle = {Proceedings of the 5th International Society for
Music Information Retrieval},
isbn = {84-88042-44-2},
keywords = {music similarity},
mendeley-tags = {music similarity},
title = {{Melodic Similarity: Looking for a Good Abstraction
Level}},
year = 2004
}