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International Symposium on Computer Music Modeling and Retrieval

CMMR 2004: Computer Music Modeling and Retrieval pp 173–192Cite as

Comparing Pitch Spelling Algorithms on a Large Corpus of Tonal Music

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3310))

Abstract

This paper focuses on the problem of constructing a reliable pitch spelling algorithm—that is, an algorithm that computes the correct pitch names (e.g., C\(\sharp\)4, B\(\flat\)5 etc.) of the notes in a passage of tonal music, when given only the onset-time, MIDI note number and possibly the duration of each note. The author’s ps13 algorithm and the pitch spelling algorithms of Cambouropoulos, Temperley and Longuet-Higgins were run on a corpus of tonal music containing 1.73 million notes. ps13 spelt significantly more of the notes in this corpus correctly than the other algorithms (99.33% correct). However, Temperley’s algorithm spelt significantly more intervals between consecutive notes correctly than the other algorithms (99.45% correct). All the algorithms performed less well on classical music than baroque music. However, ps13 performed more consistently across the various composers and styles than the other algorithms.

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Author information

Authors and Affiliations

  1. Centre for Computational Creativity, City University, London, Northampton Square, London, EC1V 0HB, United Kingdom

    David Meredith

Authors
  1. David Meredith
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Editor information

Editors and Affiliations

  1. Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Campus 55, 5230, Odense M, Denmark

    Uffe Kock Wiil

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© 2005 Springer-Verlag Berlin Heidelberg

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Meredith, D. (2005). Comparing Pitch Spelling Algorithms on a Large Corpus of Tonal Music. In: Wiil, U.K. (eds) Computer Music Modeling and Retrieval. CMMR 2004. Lecture Notes in Computer Science, vol 3310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31807-1_14

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  • DOI: https://doi.org/10.1007/978-3-540-31807-1_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24458-5

  • Online ISBN: 978-3-540-31807-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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