Statistical modeling of bowing control applied to violin sound synthesis

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Maestre E, Blaauw M, Bonada J, Guaus E, Pérez A. Statistical Modeling of Bowing Control Applied to Violin Sound Synthesis. IEEE Trans Audio Speech Lang Processing. 2010; 18(4): 855-871. DOI 10.1109/TASL.2010.2040783
http://hdl.handle.net/10230/12400
To cite or link this document: http://hdl.handle.net/10230/12400
dc.contributor.author Maestre Gómez, Esteban
dc.contributor.author Blaauw, Merlijn
dc.contributor.author Bonada, Jordi
dc.contributor.author Guaus, Enric
dc.contributor.author Pérez, Alfonso
dc.date.accessioned 2011-07-12T07:03:32Z
dc.date.available 2011-07-12T07:03:32Z
dc.date.issued 2010
dc.identifier.citation Maestre E, Blaauw M, Bonada J, Guaus E, Pérez A. Statistical Modeling of Bowing Control Applied to Violin Sound Synthesis. IEEE Trans Audio Speech Lang Processing. 2010; 18(4): 855-871. DOI 10.1109/TASL.2010.2040783
dc.identifier.issn 1558-7916
dc.identifier.uri http://hdl.handle.net/10230/12400
dc.description.abstract 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.
dc.language.iso eng
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof IEEE Transactions on Audio, Speech, and Language Processing. 2010; 18(4): 855-871
dc.rights © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5446593
dc.subject.other Violí, Música per a
dc.subject.other So -- Tractament per ordinador
dc.title Statistical modeling of bowing control applied to violin sound synthesis
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1109/TASL.2010.2040783
dc.subject.keyword Audio systems
dc.subject.keyword Signal synthesis
dc.subject.keyword Violin bowing control
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/215749
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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