A series of experiments mapping physical gesture data from the trombone to synthesis parameters.
Setup
The current prototype uses an accelerometer mounted on the bell section and a pressure sensor on the mouthpiece. Data is transmitted via Bluetooth to a Max/MSP patch running on a laptop.
Mapping Strategies
Three mapping strategies were tested:
- Direct mapping — accelerometer tilt angle controls filter cutoff frequency
- Divergent mapping — single gesture controls multiple parameters simultaneously
- Convergent mapping — multiple sensors converge to control a single synthesis parameter
Observations
The divergent mapping produced the most musically interesting results, creating a sense of the instrument "breathing" with the performer's movements. The direct mapping felt most intuitive for first-time interactions.
"The best mappings are the ones where you forget the technology is there." — a recurring theme in augmented instrument research.
Next Steps
Exploring machine learning approaches to create adaptive mappings that evolve during performance.