The Augmented String Quartet: Experiments and Gesture Following

Abstract

We present interdisciplinary research undertaken for the development of an ‘augmented’ string quartet. Hardware and software components were especially designed to enable mixed acoustic/electronic music where bow gestures drive digital sound processes. Precisely, inertial motion sensors and a bow force sensor were added to each musician's bow, and dedicated modules allowed forthe wireless data transmission to an on-line gesture analysis system. Prior to the performance, a research phase was performed to evaluate qualitatively the variability of the gesture data. Recording sessions of both gesture and audio data were carried out with a professional string quartet. The music material included a set of prototypical musical phrases containing various bowing styles and playing techniques as well as a complete music composition. The analysis of the recorded sessions allowed us to compare the consistency within and between players. While a given player was found to be generally consistent, the comparison between players revealed significant gesture idiosyncrasies. These results helped us to adapt a real-time gesture analysis system called the gesture follower. This tool was successful to automatically synchronize the live performance with electronic sound transformation in two concerts. A quantitative assessment is reported on a specific section of the piece, illustrating the accuracy and the types of errors encountered.

Acknowledgements

We warmly thank the Quatuor Danel (Marc Danel, Gilles Millet, Vlad Bogdanas, Guy Danel) for their extraordinary patience and enthusiasm during this project. The authors are grateful to the various people that were involved in this project and greatly helped us with the technology: Emmanuel Fléty, Nicolas Leroy, Matthias Demoucron, Nicolas Rasamimanana, Riccardo Borghesi, Norbert Schnell. We thank Nicolas Donin, Samuel Goldszmidt, and Maylis Dupont for their documentation work and the useful discussion around this work. We acknowledge support from the EU-IST project i-Maestro.