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Interactive Melodic Analysis

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Computational Music Analysis

Abstract

In a harmonic analysis task, melodic analysis determines the importance and role of each note in a particular harmonic context. Thus, a note is classified as a harmonic tone when it belongs to the underlying chord, and as a non-harmonic tone otherwise, with a number of categories in this latter case. Automatic systems for fully solving this task without errors are still far from being available, so it must be assumed that, in a practical scenario in which the melodic analysis is the system’s final output, the human expert must make corrections to the output in order to achieve the final result. Interactive systems allow for turning the user into a source of high-quality and high-confidence ground-truth data, so online machine learning and interactive pattern recognition provide tools that have proven to be very convenient in this context. Experimental evidence will be presented showing that this seems to be a suitable way to approach melodic analysis.

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Authors and Affiliations

  1. Universidad de Alicante, Alicante, Spain

    David Rizo, Plácido R. Illescas & José M. Iñesta

  2. Instituto Superior de Enseñanzas Artísticas de la Comunidad Valenciana (ISEA.CV), EASD, Alicante, Spain

    David Rizo

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  1. David Rizo
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  2. Plácido R. Illescas
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  3. José M. Iñesta
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Correspondence to David Rizo .

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  1. Dept. of Arch., Design & Media Tech, Aalborg University, Aalborg, Denmark

    David Meredith

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Rizo, D., Illescas, P.R., Iñesta, J.M. (2016). Interactive Melodic Analysis. In: Meredith, D. (eds) Computational Music Analysis. Springer, Cham. https://doi.org/10.1007/978-3-319-25931-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-25931-4_8

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