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Unveiling the Hierarchical Structure of Music by Multi-Resolution Community Detection Cover

Unveiling the Hierarchical Structure of Music by Multi-Resolution Community Detection

Transactions of the International Society for Music Information Retrieval
Volume 3 (2020): Issue 1
By: Jacopo de Berardinis,  Michail Vamvakaris,  Angelo Cangelosi and  Eduardo Coutinho  
Open Access
|Jun 2020

Authors

Jacopo de Berardinis

jacopo.deberardinis@manchester.ac.uk

Machine Learning and Robotics Group, Department of Computer Science, University of Manchester; Applied Music Research Lab, Department of Music, University of Liverpool

Michail Vamvakaris

michail.vamvakaris@postgrad.manchester.ac.uk

Machine Learning and Robotics Group, Department of Computer Science, University of Manchester

Angelo Cangelosi

angelo.cangelosi@manchester.ac.uk

Machine Learning and Robotics Group, Department of Computer Science, University of Manchester

Eduardo Coutinho

E.Coutinho@liverpool.ac.uk

Applied Music Research Lab, Department of Music, University of Liverpool
DOI: https://doi.org/10.5334/tismir.41 | Journal eISSN: 2514-3298
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Language: English
Submitted on: Sep 6, 2019
Accepted on: May 12, 2020
Published on: Jun 24, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Music Structure Analysis,
Music Information Retrieval,
Unsupervised Learning

© 2020 Jacopo de Berardinis, Michail Vamvakaris, Angelo Cangelosi, Eduardo Coutinho, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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