Machine learning (2018) for amplified baritone saxophone and diffused electronics


Abstract / About the project


In my piece Machine learning, I want to highlight the sound qualities of the key mechanism of the saxophone. It is amplified by several microphones on the outside, but also inside the main body of the instrument. This enabled me to access the hidden acoustic nuances of the instrument and investigate a new sonic territory, that of a sonic pallet full of various percussive sounds resonating in different ways. The goal of this project is to capture this hidden acoustic world of the instrument’s mechanism while understanding its potential for music making. Therefore, the performer is put in a place where he/she is reinvestigating the acoustic results of the traditional, common performance practices of the saxophone. The electronics are sonically intertwined with the acoustic properties of the resonant body of the instrument while expanding its acoustic and spatial possibilities. The final result is a projection of an augmented saxophone where acoustic and electronic sounds intermingle in a halo of mechanical sounds, metallic and versatile.

Machine learning (2018)


Listen here

Performance Video