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Phantom Curves: Scientific Discovery through Interactive Music Visualization

Published: 28 July 2022 Publication History

Abstract

We introduce phantom curves, a novel music-theoretical concept based on the discrete Fourier transform (DFT), and document the creative process that led to their discovery. In particular, we emphasize the importance of interactive web applications for music visualization and analysis. This is demonstrated using the example of the application midiVERTO which affords interactions with the pitch-class content of musical pieces encoded in MIDI format without requiring in-depth understanding of the underlying mathematics. We illustrate the analytical value of studying families of phantom curves by applying the concept to music from a Broadway musical, a video game, and a Hollywood movie. This process of discovery thus testifies to the fact that digital tools can bridge disciplinary boundaries between music theory and mathematics, and this interaction can generate new scientific knowledge.

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  1. Phantom Curves: Scientific Discovery through Interactive Music Visualization

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    cover image ACM Other conferences
    DLfM '22: Proceedings of the 9th International Conference on Digital Libraries for Musicology
    July 2022
    73 pages
    ISBN:9781450396684
    DOI:10.1145/3543882
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 28 July 2022

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    Author Tags

    1. discrete Fourier transform
    2. music visualization
    3. scientific discovery
    4. web application

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    Overall Acceptance Rate 27 of 48 submissions, 56%

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