Shostakovich i el violí : el Concert per a violí núm. 1 op. 77 i els Preludis op. 34

L’objectiu del projecte final titulat Shostakovich i el violí és l’estudi de la vida, el context històric i l’obra del cèlebre compositor rus Dmitri Shostakovich, parant una especial atenció en dues de les seves composicions: el Concert per a violí núm. 1 opus 77 i els Preludis per a piano opus 34 (arranjats per a violí i piano per Dmitri Tsyganov). La metodologia usada en l’elaboració del treball ha consistit en la recerca d’informació a través de biografies de Shostakovich, reculls de les seves memòries, records de persones pròximes al compositor, articles i cartes publicades per ell, així com estudis o anàlisis de les seves obres musicals. La conclusió extreta és que l’obra de Shostakovich està íntimament lligada amb el context històric en el qual va viure, és a dir, amb la seva època, tal com es pot apreciar tant en la seva escriptura com en el contingut emocional de les seves obres.

Schubert i les seves composicions per a violí

Amb aquest projecte he volgut aproximar-me al repertori de cambra per violí i piano del compositor vienès Franz Schubert. Les tres obres escollides són poc habituals a les sales de concert, en part per la seva complexitat tècnica i interpretativa, i representen tres propostes ben contrastants en la seva trajectòria compositiva. Es tracte de la introspectiva Sonatina en La menor D. 385, l’eloqüent Rondó Brillant en Si menor D. 895 i la seva obra de maduresa, la gran Fantasia en Do Major D. 934. Gràcies a l’anàlisi musical i la recerca del seu context cultural i artístic, juntament amb la meva experiència en l’instrument, he guanyat una percepció i comprensió molt més profunda de les seves obres, creixent com a persona i intèrpret amb el procés.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.

Statistical modeling of bowing control applied to violin sound synthesis

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 paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin 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 stringphysical modeling and sample-based spectral-domain synthesis.

Gesture sampling for instrumental sound synthesis: violin bowing as a case study

This paper presents a framework in which samples of bowing gesture parameters are retrieved and concatenated from a database of violin performances by attending to an annotated input score. Resulting bowing parameter signals are then used to synthesize sound by means of both a digital waveguide violin physical model, and an spectral-domainadditive synthesizer.

Statistical modeling of violin bowing parameter contours

We present a framework for modeling right-hand gestures in bowed-string instrument playing, applied to violin. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing gesture parameter cues. We model the temporal contour of bow transversal velocity, bow pressing force, and bow-bridge distance as sequences of short segments, in particular B´ezier cubic curve segments. Considering different articulations, dynamics, andcontexts, a number of note classes is defined. Gesture parameter contours of a performance database are analyzed at note-level by following a predefined grammar that dictatescharacteristics of curve segment sequences for each of the classes into consideration. Based on dynamic programming, gesture parameter contour analysis provides an optimal curve parameter vector for each note. The informationpresent in such parameter vector is enough for reconstructing original gesture parameter contours with significant fidelity. From the resulting representation vectors, weconstruct a statistical model based on Gaussian mixtures, suitable for both analysis and synthesis of bowing gesture parameter contours. We show the potential of the modelby synthesizing bowing gesture parameter contours from an annotated input score. Finally, we point out promising applicationsand developments.

Bowing the violin : a case study for auditory-motor pattern modelling in the context of music performance

This project addresses methodological and technological challenges in the development of multi-modal data acquisition and analysis methods for the representation of instrumental playing technique in music performance through auditory-motor patterning models. The case study is violin playing: a multi-modal database of violin performances has been constructed by recording different musicians while playing short exercises on different violins. The exercise set and recording protocol have been designed to sample the space defined by dynamics (from piano to forte) and tone (from sul tasto to sul ponticello), for each bow stroke type being played on each of the four strings (three different pitches per string) at two different tempi. The data, containing audio, video, and motion capture streams, has been processed and segmented to facilitate upcoming analyses. From the acquired motion data, the positions of the instrument string ends and the bow hair ribbon ends are tracked and processed to obtain a number of bowing descriptors suited for a detailed description and analysis of the bow motion patterns taking place during performance. Likewise, a number of sound perceptual attributes are computed from the audio streams. Besides the methodology and the implementation of a number of data acquisition tools, this project introduces preliminary results from analyzing bowing technique on a multi-modal violin performance database that is unique in its class. A further contribution of this project is the data itself, which will be made available to the scientific community through the repovizz platform.