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MuseReduce: A Generic Framework for Hierarchical Music Analysis
- Author(s):
- Petter Ericson, Yannis Rammos, Martin Rohrmeier
- Editor(s):
- Ailynn Ang, Jennifer Bain, David M. Weigl (see profile)
- Date:
- 2023
- Group(s):
- Music Encoding Initiative
- Subject(s):
- Digital humanities, Music
- Item Type:
- Conference paper
- Conf. Title:
- Music Encoding Conference 2022
- Conf. Org.:
- Dalhousie University
- Conf. Loc.:
- Halifax, Nova Scotia, Canada
- Conf. Date:
- May 19-22, 2022
- Tag(s):
- computational music theory, graph representation, hierarchical analysis, Music analysis, music analysis corpora, Music encoding
- Permanent URL:
- https://doi.org/10.17613/mczq-3s12
- Abstract:
- In comparison to computational linguistics, with its abundance of natural-language datasets, corpora of music analyses are rather fewer and generally smaller. This is partly due to difficulties inherent to the encoding of music analyses, whose multimodal representations—typically a combination of music notation, graphic notation, and natural language—are designed for communication between human musician-analysts, not for automated large-scale data analysis. Analyses based on hierarchical models of tonal structure, such as Heinrich Schenker’s, present additional notational and encoding challenges, since they establish relations between non- adjacent tones, and typically interpret successions of tones as expressions of abstract chordal sonorities, which may not be literally present in the music score. Building on a published XML format by Rizo and Marsden (2019), which stores analyses alongside symbolically encoded scores, this paper presents a generic graph model for reasoning about music analyses, as well as a graphical web application for creating and encoding music analyses in the aforementioned XML format. Several examples are given showing how various techniques of music analysis, primarily but not necessarily hierarchical, might be unambiguously represented through this model.
- Metadata:
- xml
- Status:
- Published
- Last Updated:
- 3 months ago
- License:
- Attribution-NonCommercial-NoDerivatives
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