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Nuanced Music Emotion Recognition via a Semi‑Supervised Multi‑Relational Graph Neural Network Cover

Nuanced Music Emotion Recognition via a Semi‑Supervised Multi‑Relational Graph Neural Network

Transactions of the International Society for Music Information Retrieval
Volume 8 (2025): Issue 1
By: Andreas Peintner,  Marta Moscati,  Yu Kinoshita,  Richard Vogl,  Peter Knees,  Markus Schedl,  Hannah Strauss,  Marcel Zentner and  Eva Zangerle  
Open Access
|Jun 2025

Authors

Andreas Peintner

andreas.peintner@uibk.ac.at

University of Innsbruck, Innsbruck

Marta Moscati

marta.moscati@jku.at

Johannes Kepler University Linz, Linz

Yu Kinoshita

e1623806@student.tuwien.ac.at

TU Wien, Wien

Richard Vogl

richard.vogl@tuwien.ac.at

TU Wien, Wien

Peter Knees

peter.knees@tuwien.ac.at

TU Wien, Wien

Markus Schedl

markus.schedl@jku.at

Johannes Kepler University Linz, Linz

Hannah Strauss

Hannah.strauss@uibk.ac.at

University of Innsbruck, Innsbruck

Marcel Zentner

Marcel.Zentner@uibk.ac.at

University of Innsbruck, Innsbruck

Eva Zangerle

eva.zangerle@uibk.ac.at

University of Innsbruck, Innsbruck
DOI: https://doi.org/10.5334/tismir.235 | Journal eISSN: 2514-3298
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Language: English
Submitted on: Oct 29, 2024
Accepted on: Apr 30, 2025
Published on: Jun 11, 2025
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
music emotion recognition,
graph neural networks,
semi-supervised learning,
contrastive loss,
evoked emotions,
node representation,
multi-relational,
genres,
tags

© 2025 Andreas Peintner, Marta Moscati, Yu Kinoshita, Richard Vogl, Peter Knees, Markus Schedl, Hannah Strauss, Marcel Zentner, Eva Zangerle, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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