• Computer-Aided Analysis Across the Tonal Divide: Cross-Stylistic Applications of the Discrete Fourier Transform

    Author(s):
    Jennifer Diane Harding
    Editor(s):
    Elsa De Luca (see profile) , Julia Flanders
    Date:
    2020
    Group(s):
    Music Encoding Initiative
    Subject(s):
    Music, Digital humanities
    Item Type:
    Conference proceeding
    Conf. Title:
    Music Encoding Conference 2020
    Conf. Org.:
    Tisch Library, Tufts University
    Conf. Loc.:
    Online
    Conf. Date:
    26-29 May 2020
    Tag(s):
    Music encoding, mei, music21
    Permanent URL:
    http://dx.doi.org/10.17613/2n0b-1v04
    Abstract:
    The discrete Fourier transform is a mathematically robust way of modeling various musical phenomena. I use the music21 Python module to interpret the pitch classes of an encoded musical score through the discrete Fourier transform (DFT). This methodology offers a broad view of the backgrounded scales and pitch-class collections of a piece. I have selected two excerpts in which the composers are very frugal with their pitch class collections—one in a tonal idiom, the other atonal. These constrained vocabularies are well suited for introducing the DFT’s methodological strengths as they pertain to score analysis.
    Notes:
    The MEC 2020 conference was originally to be hosted at Tisch Library and Lilly Music Library of Tufts University on the Medford, MA campus. It is co-sponsored with the Department of Music at Tufts, Digital Scholarship Group at Northeastern University Library, and MIT Digital Humanities.
    Metadata:
    xml
    Status:
    Published
    Last Updated:
    3 years ago
    License:
    Attribution-NonCommercial-NoDerivatives
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