Martin, CarmelGardner, HenrySwift, Ben2022-08-112022-08-11May 31 - J9781906897291http://hdl.handle.net/1885/270390We 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 experienceapplication/pdfen-AU© 2015 The Author/shttps://creativecommons.org/licenses/by/4.0mobile musicensemble performancemachine learningtransition matricesgesture201510.5281/zenodo.11791302021-08-01Creative Commons Attribution 4.0 International