Tracking Ensemble Performance on Touch-Screens with Gesture Classification and Transition Matrices

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Martin, Carmel
Gardner, Henry
Swift, Ben

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Goldsmiths University of London

Abstract

We present and evaluate a novel interface for tracking ensemble performances on touch-screens. The system uses a Random Forest classifier to extract touch-screen gestures and transition matrix statistics. It analyses the resulting gesture-state sequences across an ensemble of performers. A series of specially designed iPad apps respond to this real-time analysis of free-form gestural performances with calculated modifications to their musical interfaces. We describe our system and evaluate it through cross-validation and profiling as well as concert experience

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Proceedings of the International Conference on New Interfaces for Musical Expression

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Open Access

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Creative Commons Attribution 4.0 International

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