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Measuring social interaction in music ensembles
Gualtiero Volpe1, Alessandro D'Ausilio2, Leonardo Badino2
1Casa Paganini-InfoMus, DIBRIS, Università degli Studi di Genova, Viale Causa 13, Genova 16145, Italy gualtiero.volpe@unige.it.
Abstract:
Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances.
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