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Encoding and Analyzing the Timbre in Popular Songs (TiPS) Corpus
- Author(s):
- Nicole Biamonte, Ben Duinker, Lindsey Reymore, Jade Roth, Nicholas Shea, Jeremy Tatar, Leigh VanHandel, Christopher William White, Matthew Zeller
- 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 poster
- Conf. Title:
- Music Encoding Conference 2022
- Conf. Org.:
- Dalhousie University
- Conf. Loc.:
- Halifax, Nova Scotia, Canada
- Conf. Date:
- May 19-22, 2022
- Tag(s):
- form, genre, Music encoding, Popular music, texture, timbre
- Permanent URL:
- https://doi.org/10.17613/y623-gk42
- Abstract:
- Timbre and texture are important and perceptually salient stylistic and structural parameters in popular music, yet their specific functional roles in this repertoire have not been theorized. This report describes the construction and encoding of a new popular-music corpus, Timbre in Popular Song (TiPS). The corpus comprises 400 songs, including 100 songs each from four disparate genres: country, pop, heavy metal, and hip hop. Song selection in TiPS balances genre typicality with considerations of gender and racial diversity as well as chronological representation; details related to timbre, texture, and form for each song are being encoded and will be analyzed by genre to identify normative timbral and textural combinations, as well as typical differences among genres.
- Notes:
- Tied Winner of the MEC 2022 People's Choice - Best Poster Award
- Metadata:
- xml
- Status:
- Published
- Last Updated:
- 3 months ago
- License:
- Attribution-NonCommercial-NoDerivatives
mec22_139-144_reymore.pdf