Performance with Esteso: Interactive AI Music Duet Based on Player-Idiosyncratic Extended Double Bass Techniques
Year: 2025
Type: conference-paper
Abstract: Esteso is an interactive improvisational system for double-bass based on player-idiosyncratic extended techniques. It was created in collaboration with the contemporary double-bass player and composer Filippo Angeloni and tailored for his personal vocabulary of extended techniques. In Esteso, the musician and an AI counterpart take turns in an improvisational duet. The system's response consists of a manipulation of the real double-bass, achieved live through a timbre-transfer neural network, granular synthesis, and reverberation. The timbre-transfer network was trained on generic double-bass recordings, resulting in a peculiar 'hybrid' double-bass sound. We Machine listening is integrated in the form of a real-time classifier of extended techniques played on the double-bass, whose output controls the sound manipulation process to affect various techniques differently. The personal extended techniques chosen for Esteso are: 'Brushed' Jeté, Sfregato con legno, and Percussive. Here, we propose a 10/15 minutes improvised duet performance where the double bass player interacts with Esteso, creating an action-reaction interplay between acoustic and virtual.
Authors: Angeloni, Filiippo, Stefani, Domenico, Tomasetti, Matteo
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912197177
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