Measuring the Structural Complexity of Music: From Structural Segmentations to the Automatic Evaluation of Models for Music Generation-Reference-Cited by-同舟云学术

Measuring the Structural Complexity of Music: From Structural Segmentations to the Automatic Evaluation of Models for Music Generation

Published:2022 Issue: Volume:30 Page:1963-1976
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

de Berardinis Jacopo¹^ORCID,Cangelosi Angelo²^ORCID,Coutinho Eduardo³^ORCID

Affiliation:

1. King's College London, University of Liverpool, Liverpool, U.K.

2. Machine Learning and Robotics Group (MLR), Department of Computer Science, University of Manchester, Manchester, U.K.

3. Applied Music Research Lab (AMLAB), Department of Music, University of Liverpool, Liverpool, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

http://xplorestaging.ieee.org/ielx7/6570655/9657755/09787343.pdf?arnumber=9787343

Reference61 articles.

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2. Music transcription modelling and composition using deep learning;sturm,2016

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

4. Using quadratic programming to estimate feature relevance in structural analyses of music

5. Automatic audio segmentation using a measure of audio novelty

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