ECHO - Embodied Counterpoint & Human-Machine Ontology. An exploration of AI training in piano performance and pedagogy
The ECHO project explores the intersection of artificial intelligence (AI), biosensors, and piano performance practice at an embodied level. The objective is to address the role of the body and its perceptual system in the “counterpoint” between human and machine interaction and its ontology, which is an urgent challenge for the advancement of AI applications in music performance practice. This investigation is an extension of my previous research (T*ActILE and Encounters) and the CREATIE research group project AI-Musicking. It also constitutes the preliminary work of my proposed ERC project, which, if accepted, will be integrated into this two-year project’s budget starting in 2026. The method entails a series of artistic and scientific experiments conducted in cooperation with RCA researchers and piano students, as well as external labs: IMEC-University Antwerp, IPEM-University Ghent, VUB-Brussels, and LWT3 Milano. The aim is to study the real-time feedback and adaptive learning experiences of biosensors in monitoring muscle tension during piano performance. The embodied dataset will be integrated into an AI model to improve piano technique, reduce the risk of injuries, and create novel interactive performances. The outcome will consist of a methodology useful for piano education and performance creation, which will be shared through workshops, seminars, conferences, lecture-performances, CD of all Philip Glass Etudes reworked with AI and an article. The insights gained will contribute to personalized piano education methodologies for students and advanced pianists and new creations.
Results
The project’s output will provide valuable scientific and artistic outcomes into AI technology that will
contribute to shaping future scenarios in piano education and creation. In concrete terms, the project is expected to yield the following deliverables: 1.Platforms for Scientific and Artistic Data Preservation; 2.
Interactive AI application and Wearables Sensors for motion-tensions recognition for educational and artistic purposes; 3. Academic Publications; 5. Workshops and Events; 6. Artistic Projects and Multidisciplinary
Performances in collaboration with a series of performance spaces; 7. Industrial Design: tailored WINGS suits and development of new wearable sensors.
The output will address the growing demand in Conservatoires and Academies on concrete applications of AI
for music education and for creation by delivering, in collaboration with LWT3 Lab, a tailored armband
wearable sensors for pianists, that substitute the old MYO armband technology, which has also been lacking. Outlooks are future implementations of these methods and the AI tool to monitor the practicing of other instruments and other performing disciplines, like dance.
