Playability evaluation of a virtual bowed string instrument
NIME '03 Proceedings of the 2003 conference on New interfaces for musical expression
Bézier Spline Modeling of Pitch-Continuous Melodic Expression and Ornamentation
Computer Music Journal
Combining accelerometer and video camera: reconstruction of bow velocity profiles
NIME '06 Proceedings of the 2006 conference on New interfaces for musical expression
Expressive concatenative synthesis by reusing samples from real performance recordings
Computer Music Journal
Gesture analysis of violin bow strokes
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Learning and extraction of violin instrumental controls from audio signal
Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
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Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigms would benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. We present a framework for modeling bowing control parameters in violin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals. We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed string physical modeling and sample-based spectral-domain synthesis.