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.
Titolo: | Measuring social interaction in music ensembles |
Autori: | FADIGA, Luciano (Ultimo) |
Data di pubblicazione: | 2016 |
Rivista: | |
Handle: | http://hdl.handle.net/11392/2351705 |
Appare nelle tipologie: | 03.1 Articolo su rivista |
File in questo prodotto:
File | Descrizione | Tipologia | Licenza | |
---|---|---|---|---|
rstb.2015.0377.pdf | Full text (versione editoriale) | PUBBLICO - Pubblico con Copyright | Open Access Visualizza/Apri |