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arXiv · 2012.00296

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

Charles Martin·Henry Gardner·Ben Swift
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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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Charles Martin, Henry Gardner, Ben Swift. 2020-12-01. Tracking Ensemble Performance on Touch-Screens with Gesture Classification and Transition Matrices. https://doi.org/10.5281/zenodo.1179130

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