publication . Other literature type . Conference object . 2016

Can Machine Learning Apply To Musical Ensembles?

Martin, Charles; Gardner, Henry;
Open Access
  • Published: 08 May 2016
  • Publisher: Zenodo
Abstract
In this paper we ask whether machine learning can apply to musical ensembles as well as it does to the individual musical interfaces that are frequently demonstrated at NIME and CHI. While using machine learning to map individual gestures and sensor data to musical output is becoming a major theme of computer music research, these techniques are only rarely applied to ensembles as a whole. We have developed a server-based system that tracks the touch-data of an iPad ensemble and have used such techniques to identify touch-gestures and to characterise ensemble interactions in real-time. We ask whether further analysis of this data can reveal unknown dimensions of...
Subjects
ACM Computing Classification System: InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI)
free text keywords: Machine Learning, Musical Ensembles, Performance, HCI, Computer Music
Download fromView all 2 versions
Zenodo
Other literature type . 2016
Provider: Datacite
ZENODO
Conference object . 2016
Provider: ZENODO
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Other literature type . Conference object . 2016

Can Machine Learning Apply To Musical Ensembles?

Martin, Charles; Gardner, Henry;