Performance with Esteso: Interactive AI Music Duet Based on Player-Idiosyncratic Extended Double Bass Techniques

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-14
DOI
https://doi.org/10.5281/zenodo.15028088
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Performance with Esteso: Interactive AI Music Duet Based on Player-Idiosyncratic Extended Double Bass Techniques

Zenodo (CERN European Organization for Nuclear Research)
Music Technology and Sound Studies
article

Performance with Esteso: Interactive AI Music Duet Based on Player-Idiosyncratic Extended Double Bass Techniques

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Music Technology and Sound Studies
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Performance with Esteso: Interactive AI Music Duet Based on Player-Idiosyncratic Extended Double Bass Techniques · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS