Comparing Pitch Spelling Algorithms on a Large Corpus of Tonal Music

  • David Meredith
Conference paper

DOI: 10.1007/978-3-540-31807-1_14

Volume 3310 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
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

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • David Meredith
    • 1
  1. 1.Centre for Computational CreativityCity University, LondonLondonUnited Kingdom