Computational analysis of solo versus ensemble performance in string quartets: intonation and dynamics

dc.contributor.author
Papiotis, Panagiotis, 1985-
dc.contributor.author
Marchini, Marco, 1984-
dc.contributor.author
Maestre Gómez, Esteban
dc.date.issued
2017-05-16T08:34:44Z
dc.date.issued
2017-05-16T08:34:44Z
dc.date.issued
2012
dc.identifier
Papiotis P, Marchini M, Maestre E. Computational analysis of solo versus ensemble performance in string quartets: intonation and dynamics. In: Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music; 2012 July 23-28; Thessaloniki, Greece. [place unknown]: ICMPC – ESCOM 2012; 2012. [7 p.].
dc.identifier
http://hdl.handle.net/10230/32130
dc.description.abstract
Comunicació presentada a la conferència conjunta que inclou la 12th International Conference on Music Perception and Cognition (ICMPC) i la 8th Triennial Conference of the European Society, celebrada a Tessalònica (Grècia) els dies 23 a 28 de juliol de 2012.
dc.description.abstract
Musical ensembles, such as a string quartet, are a clear case of music performance where a joint interpretation of the score as well as joint action during the performance is required by the musicians. Of the several explicit and implicit ways through which the musicians cooperate, we focus on the acoustic result of the performance – in this case in terms of dynamics and intonation - and attempt to detect evidence of interdependence among the musicians by performing a computational analysis. We have recorded a set of string quartet exercises whose challenge lies in achieving ensemble cohesion rather than correctly performing one’s individual task successfully, which serve as a ‘ground truth’ dataset; these exercises were recorded by a professional string quartet in two experimental conditions: solo, where each musician performs their part alone without having access to the full quartet score, and ensemble, where the musicians perform the exercise together following a short rehearsal period. Through an automatic analysis and post-processing of audio and motion capture data, we extract a set of low-level features, on which we apply several numerical methods of interdependence (such as Pearson correlation, Mutual Information, Granger causality, and Nonlinear coupling) in order to measure the interdependence -or lack thereofamong the musicians during the performance. Results show that, although dependent on the underlying musical score, this methodology can be used in order to automatically analyze the performance of a musical ensemble.
dc.description.abstract
The work presented on this document has been partially supported by the EU-FP7 FET SIEMPRE project and an AGAUR research grant from Generalitat de Catalunya.
dc.format
application/pdf
dc.format
application/pdf
dc.language
eng
dc.publisher
12th International Conference on Music Perception and Cognition (ICMPC) - 8th Triennial Conference of the European Society
dc.relation
Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music; 2012 July 23-28; Thessaloniki, Greece. [place unknown]: ICMPC – ESCOM 2012; 2012. [7 p.].
dc.relation
info:eu-repo/grantAgreement/EC/FP7/250026
dc.rights
© 12th International Conference on Music Perception and Cognition (ICMPC)- 8th Triennial Conference of the European Society
dc.rights
info:eu-repo/semantics/openAccess
dc.subject
Enginyeria acústica
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So -- Enregistrament i reproducció
dc.title
Computational analysis of solo versus ensemble performance in string quartets: intonation and dynamics
dc.type
info:eu-repo/semantics/conferenceObject
dc.type
info:eu-repo/semantics/publishedVersion


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