The Nuremberg University of Music wins the "AI-supported real-time feedback for movement gestures - MOTION.KI" project in the "NewNormal KI" funding programme with the project proposal by Prof. Dr Sebastian Trump. The "NewNormal KI" funding programme was initiated by the Bavarian Ministry of Science and supports Bavarian universities in the closer integration of analogue and digital teaching/learning formats with the use of AI.
MOTION.KI places movement gestures as the centrepiece of musical communication at the heart of teaching - especially in percussion/conducting and elemental music-making practice. Since targeted practice of conducting and percussion movements is often only possible to a limited extent outside of classroom teaching, the project closes this gap through AI-based real-time feedback: movement and sound gestures are visibly or audibly fed back and can thus also be specifically trained in self-directed practice phases.
Technically, MOTION.KI builds on the Music Motion Tools developed at the NUM in the RE|LEVEL sub-project and uses them to develop browser-based, installation-free practice and teaching tools with camera-based motion tracking. One core component is a modular basic percussion/conducting course that interlinks presence, hybrid formats and asynchronous practice; in addition, an application scenario for EMP is being developed in which body and object gestures shape sound parameters in real time. Software and teaching modules will be published as OER/OSS and expanded to include authoring functions for teachers.
The didactic development, evaluation and transfer will take place across universities in cooperation with Prof. Dr Johannes Hasselhorn (Chair of Music Pedagogy and Didactics, Friedrich-Alexander University Erlangen-Nuremberg) in the context of ensemble conducting lessons and with Prof. Michael Forster (Professor of Elemental Music Pedagogy, Nuremberg University of Music Würzburg) for tests and piloting in EMP-specific Music Practice.
Share