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A music information retrieval approach to Pop music culture

A music information retrieval approach to Pop music culture

Arthur Flexer (ORCID: 0000-0002-1691-737X)
  • Grant DOI 10.55776/P36653
  • Funding program Principal Investigator Projects
  • Status ongoing
  • Start June 1, 2023
  • End May 31, 2026
  • Funding amount € 403,452

Disciplines

Other Humanities (10%); Computer Sciences (70%); Arts (20%)

Keywords

    Music Information Retrieval, Pop Music, Machine Learning, Digital Musicology

Abstract

Pop music is one of the most popular forms of music around the world, enjoyed by millions of people every day. It is a cultural phenomenon that reflects the changing tastes, attitudes, and experiences of society, and has a profound impact on the way we see and understand the world around us. However, despite its popularity and significance, there is still much we do not know about Pop music as a cultural entity and about the social and cultural context in which it is produced and consumed. To help answer such questions, we are using Music Information Retrieval (MIR) methods to study Western Pop music culture at a large scale. MIR is an interdisciplinary field that involves using advanced technology and computer methods to extract information from music, which includes signal processing, machine learning, and artificial intelligence. Our approach is reminiscent of "distant reading", which means using algorithmic analysis of thousands of books as a research tool in digital humanities. We will also use "distant listening" to audio using MIR methods, "distant viewing" of album artwork via object recognition, and "distant reading" of meta-information, lyrics, magazines, and books using natural language processing. These "distant" computer methods allow to study much greater numbers of songs, images and texts than individual experts are able to analyze. An integrative multi-modal approach is important because Pop music is not just about the music itself, but also about the cultural and social meanings that it carries. Our main goal is to critically appraise MIR`s ability to provide empirical evidence to existing Pop music theories from humanities. We will provide exemplary results concerning a number of questions in a data-driven manner. For example, can we chart the universe of topics in music lyrics? Can we compute an iconography of album cover art? Can we find evidence for retro cycles in Pop music`s development? What is the influence of subcultures on mainstream music? By answering these questions, we hope to gain a deeper understanding of Pop music and its place in society. We will also need to be aware of the principal limitations of distant reading/listening/viewing and precisely research and document these boundaries. This project will open up a new sub-field of MIR on the empirical and quantitative study of Pop music culture. This new sub-field will also help to establish a digital humanities approach to Pop music culture, which will help us to understand this cultural phenomenon in a more comprehensive way.

Research institution(s)
  • Universität Linz - 100%
Project participants
  • Natalia Wächter, Universität Graz , national collaboration partner
  • Isabella Czedik-Eysenberg, Universität Wien , national collaboration partner

Research Output

  • 1 Citations
  • 5 Publications
Publications
  • 2023
    Title A Review of Validity and Its Relationship to Music Information Research
    DOI 10.5281/zenodo.10265219
    Type Conference Proceeding Abstract
    Author Arthur Flexer
    Link Publication
  • 2024
    Title Charting the Universe of Metal Music Lyrics and Analyzing Their Relation to Perceived Audio Hardness
    DOI 10.5334/tismir.182
    Type Journal Article
    Author Czedik-Eysenberg I
    Journal Transactions of the International Society for Music Information Retrieval
    Link Publication
  • 2024
    Title Image analysis of Pop music cover album art
    Type Other
    Author Selene Ximena Andrade López
    Link Publication
  • 2024
    Title On the Validity of Employing ChatGPT for Distant Reading of Music Similarity
    Type Conference Proceeding Abstract
    Author Arthur Flexer
    Conference 25th International Society for Music Information Retrieval Conference
    Link Publication
  • 2023
    Title Can ChatGPT Be Useful for Distant Reading of Music Similarity?
    Type Conference Proceeding Abstract
    Author Arthur Flexer
    Conference 2nd Workshop on Human-Centric Music Information Research
    Link Publication

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