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Automatic Classification of Leading Interactions in a String Quartet

Authors:

Floriane Dardard,

Giorgio Gnecco,

Donald GlowinskiAuthors Info & Claims

ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 6, Issue 1

Article No.: 5, Pages 1 - 27

https://doi.org/10.1145/2818739

Published: 09 March 2016 Publication History

Abstract

The aim of the present work is to analyze automatically the leading interactions between the musicians of a string quartet, using machine-learning techniques applied to nonverbal features of the musicians’ behavior, which are detected through the help of a motion-capture system. We represent these interactions by a graph of “influence” of the musicians, which displays the relations “is following” and “is not following” with weighted directed arcs. The goal of the machine-learning problem investigated is to assign weights to these arcs in an optimal way. Since only a subset of the available training examples are labeled, a semisupervised support vector machine is used, which is based on a linear kernel to limit its model complexity. Specific potential applications within the field of human-computer interaction are also discussed, such as e-learning, networked music performance, and social active listening.

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Cited By

Clayton MJakubowski KEerola T(2019)Interpersonal entrainment in Indian instrumental music performance: Synchronization and movement coordination relate to tempo, dynamics, metrical and cadential structureMusicae Scientiae10.1177/102986491984480923:3(304-331)Online publication date: 20-Jul-2019
https://doi.org/10.1177/1029864919844809
Gnecco G(2018)Symmetric and antisymmetric properties of solutions to kernel-based machine learning problemsNeurocomputing10.1016/j.neucom.2018.04.016306:C(141-159)Online publication date: 6-Sep-2018
https://dl.acm.org/doi/10.1016/j.neucom.2018.04.016
Schaerlaeken SGrandjean DGlowinski D(2017)Playing for a Virtual Audience: The Impact of a Social Factor on Gestures, Sounds and Expressive IntentsApplied Sciences10.3390/app71213217:12(1321)Online publication date: 19-Dec-2017
https://doi.org/10.3390/app7121321
Show More Cited By

Index Terms

Automatic Classification of Leading Interactions in a String Quartet
1. Computing methodologies
  1. Machine learning

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Information & Contributors

Information

Published In

cover image ACM Transactions on Interactive Intelligent Systems

ACM Transactions on Interactive Intelligent Systems Volume 6, Issue 1

Special Issue on New Directions in Eye Gaze for Interactive Intelligent Systems (Part 2 of 2), Regular Articles and Special Issue on Highlights of IUI 2015 (Part 1 of 2)

May 2016

219 pages

ISSN:2160-6455

EISSN:2160-6463

DOI:10.1145/2896319

Editors:
Anthony Jameson
German Research Center for Artifi cial Intelligence (DFKI), Germany
,
Krzysztof Gajos
Harvard University, U.S.A.

Issue’s Table of Contents

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 March 2016

Accepted: 01 November 2015

Revised: 01 November 2015

Received: 01 March 2015

Published in TIIS Volume 6, Issue 1

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Future and Emerging Technologies (FET) program within the 7th Framework Programme for Research of the European Commission, under FET-Open

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Cited By

Clayton MJakubowski KEerola T(2019)Interpersonal entrainment in Indian instrumental music performance: Synchronization and movement coordination relate to tempo, dynamics, metrical and cadential structureMusicae Scientiae10.1177/102986491984480923:3(304-331)Online publication date: 20-Jul-2019
https://doi.org/10.1177/1029864919844809
Gnecco G(2018)Symmetric and antisymmetric properties of solutions to kernel-based machine learning problemsNeurocomputing10.1016/j.neucom.2018.04.016306:C(141-159)Online publication date: 6-Sep-2018
https://dl.acm.org/doi/10.1016/j.neucom.2018.04.016
Schaerlaeken SGrandjean DGlowinski D(2017)Playing for a Virtual Audience: The Impact of a Social Factor on Gestures, Sounds and Expressive IntentsApplied Sciences10.3390/app71213217:12(1321)Online publication date: 19-Dec-2017
https://doi.org/10.3390/app7121321
Glowinski DBracco FChiorri CGrandjean D(2016)Music Ensemble as a Resilient System. Managing the Unexpected through Group InteractionFrontiers in Psychology10.3389/fpsyg.2016.015487Online publication date: 7-Oct-2016
https://doi.org/10.3389/fpsyg.2016.01548
Gnecco G(2016)Symmetry and antisymmetry properties of optimal solutions to regression problemsOptimization Letters10.1007/s11590-016-1101-x11:7(1427-1442)Online publication date: 21-Dec-2016
https://doi.org/10.1007/s11590-016-1101-x

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