Abstract
This paper describes an empirical approach to evaluating similarity measures for the comparision of two note sequences or melodies. In the first sections the experimental approach and the empirical results of previous studies on melodic similarity are reported. In the discussion section several questions are raised that concern the nature of similarity or distance measures for melodies and musical material in general. The approach taken here is based on an empirical comparision of a variety of similarity measures with experimentally gathered rating data from human music experts. An optimal measure is constructed on the basis of a linear model.
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Müllensiefen, D., Frieler, K. (2006). Evaluating Different Approaches to Measuring the Similarity of Melodies. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_32
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DOI: https://doi.org/10.1007/3-540-34416-0_32
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