Abstract
We explore whether large language models (ChatGPT) can be used as a ‘distant reading’ tool to estimate
music similarity between songs from textual information, complementing experiments with human
participants. We compare degrees of rater agreement to previous results from a listening test, showing
that correlation of ChatGPT with human raters is significantly lower than the average human inter-rater
agreement, but nevertheless still of moderate positive size. We discuss whether an approach based on
the largely opaque ChatGPT model can be scientifically valid and to what extent it allows transparent
evaluation of music information research experiments.
Original language | English |
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Title of host publication | HCMIR23: 2nd Workshop on Human-Centric Music Information Research |
Number of pages | 6 |
Publication status | Published - Nov 2023 |
Fields of science
- 202002 Audiovisual media
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
JKU Focus areas
- Digital Transformation