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A General Parsing Model for Music and Language

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Music and Artificial Intelligence (ICMAI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2445))

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Abstract

Is there a general mechanism that governs the perception of phrase structure in music and language? While it is usually assumed that humans have separate faculties for music and language, this work focuses on the commonalities rather than on the differences between these modalities, aiming at finding a deeper “faculty”. We present a series of data-oriented parsing (DOP) models which aim at balancing the simplest structure with the most likely structure of an input. Experiments with the Essen Folksong Collection and the Penn Treebank show that exactly the same model with the same parameter setting achieves maximum parse accuracy for both music and language. This suggests an interesting parallel between musical and linguistic processing. We show that our results outperform both the melodic component of Temperley (2001) and the musical parser of Bod (2001b).

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Author information

Authors and Affiliations

  1. Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam

    Rens Bod

  2. School of Computing, University of Leeds, Leeds

    Rens Bod

Authors
  1. Rens Bod
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Editor information

Editors and Affiliations

  1. Faculty of Music, University of Edinburgh, 12 Nicolson Square, EH8 9DF, Edinburgh, UK

    Christina Anagnostopoulou  & Miguel Ferrand  & 

  2. Division of Informatics, University of Edinburgh, 80 South Bridge, EH1 1HN, Edinburgh, UK

    Alan Smaill

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© 2002 Springer-Verlag Berlin Heidelberg

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Bod, R. (2002). A General Parsing Model for Music and Language. In: Anagnostopoulou, C., Ferrand, M., Smaill, A. (eds) Music and Artificial Intelligence. ICMAI 2002. Lecture Notes in Computer Science(), vol 2445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45722-4_3

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  • DOI: https://doi.org/10.1007/3-540-45722-4_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44145-8

  • Online ISBN: 978-3-540-45722-0

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