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Cited by 1Music Technology and Sound StudiesMusic History and CultureMusicology and Musical Analysis

Digital discourse and the human experiences of AI music: an ethnomusicological perspective

Open access
Avdeeff, Melissa·2025·Ethnomusicology Forum
DOI 10.1080/17411912.2025.2551437
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Abstract

When Anna Indiana, the self-proclaimed first AI singer songwriter, released her debut track, ‘Betrayed by this Town’, on Twitter/X in November 2023, the response was overwhelmingly negative. A comm...

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Crossref · 10.1080/17411912.2025.2551437

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10 of 10 references verified0 citation errors · 0 not checkable

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  • The central hypothesis that transforming oral narratives into song enhances their memorability and emotional resonance finds substantial support in the cognitive and psychological literature, though the evidence reveals important conditionalities.

    “The central hypothesis of this methodology -that transforming oral narratives into song enhances their memorability and emotional resonance -finds substantial support in the cognitive and psychological literature, though the evidence reveals important conditionalities that must inform the design of the proposed process.”

    From From Oral to Aural: A Community-Led Methodology for Documenting Place-Based Histories through Narrative and AI-Generated Song (2026) · cites this paper as [3]

    Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

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  • One study reported significantly higher lyric recall in the music condition during immediate testing and a delayed advantage after one week.

    “One study reported significantly higher lyric recall in the music condition during immediate testing and a delayed advantage after one week, suggesting that the mnemonic benefit of song persists beyond short-term memory windows [3].”

    From From Oral to Aural: A Community-Led Methodology for Documenting Place-Based Histories through Narrative and AI-Generated Song (2026) · cites this paper as [3]

    The Introduction discusses digital discourse and ethnomusicological methods for studying AI music, not an experiment on lyric recall. Searches of our copy for immediate and one-week testing, and for songs’ mnemonic benefits, found no passage reporting the attributed result. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 4

  1. Fraser, Jennifer and Gabriela Linares. 2023. ‘Reimagining the Representation of Ethnographic Knowledge: The Philosophy and Methodology of a Digital Humanities Project’. In Open Access Musicology: Volume Two, edited by Daniel Barolsky and Louis Epstein, 33–68. Ann Arbor: Lever Press.
  2. Simpson, Audra and Andrea Smith. 2014. Theorizing Native Studies. Durham, NC: Duke University Press.
  3. Solis, Gabriel. 2017. ‘Music Technology in Ethnomusicology’. In The Oxford Handbook of Technology and Music Education, edited by S. Alex Ruthmann and Roger Mantie, 57–64. New York: Oxford University Press.
  4. Tzanetakis, George, Ajay Kapur, W. Andrew Schloss and Matthew Wright. 2007. ‘Computational Ethnomusicology’. Journal of Interdisciplinary Music Studies 1(2): 1–24.

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Authors
Avdeeff, M.
Affiliations
University of Stirling (GB)
Corresponding author
Avdeeff, Melissa
ORCID
Avdeeff, Melissa
Venue
Ethnomusicology Forum
Publisher
Informa UK Limited
Published
2025-05-04
Volume
34
Issue
2
Pages
219-224
ISSN
  • 1741-1912 (ISSN-L)
  • 1741-1920
DOI
10.1080/17411912.2025.2551437
OpenAlex
W4416650775
Cited by
0
References
10
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
Locations
Ethnomusicology Forum (publishedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Music Technology and Sound Studies
  • Social Sciences › Arts and Humanities › Music › Music History and Culture
  • Social Sciences › Arts and Humanities › Music › Musicology and Musical Analysis
Keywords
digital discourse, music and technology, social media reactions

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