The OpenTuning ANR project focuses on enhancing Human-Computer Interaction (HCI) in the field of generative music systems. It aims to empower artists by offering highly customizable tools that adapt to individual creative practices. The project builds on the principle of practice-oriented design, where users actively shape both the tool and the artistic outcomes, enabling a high degree of personalization in music creation through machine teaching.
The main research objectives are:
1. Develop adaptive systems that allow musicians, whether experts or novices, to fine-tune generative music tools based on their personal preferences by providing small sets of curated data representing their idea of the relationship between system inputs and outputs;
2. Model the relationship between control inputs and musical outputs through customizable algorithms and the development of multi-scale audio perception modules for real-time musical interaction ;
3. Assess how these systems contribute to creative individuation, where the act of teaching the machine refines the user’s artistic vision.
The project will combine theoretical and experimental phases with field studies. Through collaboration with international artists and real-life applications, OpenTuning will draw on a participatory observation approach in creative production contexts as well as in pedagogical settings. It will seek to propose frameworks applicable to other fields of human-computer interaction, including interactive media, education, pedagogy and collaborative technologies, by tackling the problem of meaningful interaction with generative systems through “machine teaching” and the participative design of generative musical systems.
Référence projet : ANR-25-CE33-0123
