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Designing a non-invasive and removable bow augmentation

A research project in collaboration with Vincent Cusson

with the support of the CIRMMT Student Award

Context of research

Although many violin augmented-bows implementing sensors using inertial movement units have been designed in the past twenty years, most of them share common draw-backs: their bulkiness, their invasiveness forcing the performer to adapt their playing to the bow, the absence of sensors to capture essential playing information such as pressure or rotation, their obscure software implementation, and their cost and difficult reproducibility. Moreover, most existing augmented bows focus on differences in articulation, string and pitch, which limits the user to a rather traditional playing style. It seemed necessary to design an augmented bow which would take into account string instrument playing techniques that are now common in contemporary classical music, such as

col legno, circular bows, overpressure, etc.

Comparison of some existing augmented bows

Objectives

The goal of an augmented bow is to capitalize both on the large gestural variety inherent to string instruments playing, as well as an augmented bow would make possible the control of the electronics without adding parasitical movements which could impair the traditional playing as well as the comfort of the musician. Adding buttons, pedals and other controllers external to the musician’s playing asks for an additional expertise, which in turn can reduce both the performance quality and the accessibility of mixed music works. The cognitive load added by such controllers can be reduced by a non-invasive augmented bow. Secondly, this augmented bow would recognize specific gestures from the musician. This recognition can serve the control of the electronics, but can also be a useful tool in education and research. Lastly, most of bow movements include a preparation which is intimately linked to the sound result. A soft attack, a jeté, or a col legno battuto (hitting the string with the wood of the bow) do not require the same type of preparation. The gestures could therefore be recognized—or at least predicted with a certain precision to be determined—before they happen. Such anticipation of gestures could serve for gesture following

and for synchronizing the electronics with the performer’s playing.

The objectives of this research can be summarized by the four following goals:

design a non-invasive and removable module for augmenting a bow
develop data parsing and gestural recognition algorithm which does not need prior training
create a transparent and malleable software interface to map gestures to sound events and processes
improvise, compose and perform music using the augmented bow

References

1. R. Alonso Trillo, P. Nelson, and T. Michailidis. Rethinking Instrumental Interface Design: The Metabow. Computer Music Journal, 47, 2 (2023): 5-20.

2. E. Guaus, J. Bonada, A. Perez, E. Maestre, and M. Blaauw. Measuring the Bow Pressing Force in Real Violin Performance. International Symposium on Musical Acoustics (ISMA), Barcelona, Spain, 2007.

3. M. Kimura, N. Rasamimanana, F. Bevilacqua, N. Schnell, B. Zamborlin, and E. Fléty. Extracting Human Expression for Interactive Composition with the Augmented Violin. Proceedings of the International Conference on New Interfaces for Musical Expression, University of Michigan, Ann Arbor, Michigan, USA, 2012.

4. M. Marchini, P. Papiotis, A. Perez, and E. Maestre. Gesture Sampling for Instrumental Sound Synthesis: Violin Bowing as a Case Study. International Conference on Mathematics and Computing, Chennai, TamilNadu, India, 2010.

5. K. McMillen. Stage-Worthy Sensor Bows for Stringed Instruments. Proceedings of the International Conference on New Interfaces for Musical Expression, Genoa, Italy, 2008.

6. N. Rasamimanana, E. Fléty, and F. Bevilacqua. Gesture Analysis of Violin Bow Strokes. Proceedings of the Gesture in Human-Computer Interaction and Simulation Conference, Berder Island, France, 2005

7. N. Rasamimanana and F. Bevilacqua. Effort-Based Analysisof Bowing Movements: Evidence of Anticipation Effects.Journal of New Music Research, 37, 4 (2010).

8. E. Schoonderwaldt, and M. Demoucron. Extraction of Bowing Parameters from Violin Performance Combining Motion Capture and Sensors. The Journal of the Acoustical Society of America, 126, 5 (2009), 2695-708.

9. D. Young. The Hyperbow Controller: Real-Time Dynamics Measurement of Violin Performance. Proceedings of the International Conference on New Interfaces for Musical Expression, Dublin, Ireland, 2002.