An Empirical Investigation of Bow-Force Limits in the Schelleng Diagram

Schoonderwaldt, Erwin; Guettler, Knut; Askenfelt, Anders

doi:10.3813/aaa.918070

Cited by 21 publications

(38 citation statements)

References 9 publications

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“…As pointed out by Schoonderwaldt et al, 15 there was a higher degree of uncertainty associated with the determination of the lower bow-force limit, which was shown to be strongly influenced by finger damping. As this was an uncertain factor in the current experiment, the location of the lower bow-force limit could not be exactly estimated.…”

Section: A Sustained Notesmentioning

confidence: 86%

“…The lower bow-force limit is therefore indicated by a band, representing the range of lower limits found under different conditions reported in that study. 15 Another assumption based on the earlier findings is that the lower limit is independent of bow velocity, in contrast to Schelleng's predictions. This behavior is extrapolated to bow velocities of 25 and 30 cm/s, not measured in the earlier study.…”

Section: A Sustained Notesmentioning

confidence: 92%

“…The limits of the playable region were estimated for the same violin and same type of string ͑Pirastro Obligato, D string stopped at pitch G4͒, with the use of a bowing machine. Additional information regarding the upper and lower bow-force limits is based on the findings by Schoonderwaldt et al 15 ͑see figure caption and footnote 17 for more details͒.…”

Section: Coordination Of Bowing Parameters In the Schelleng Diagrammentioning

confidence: 99%

“…The chosen combinations of bowing parameters by the participating players can be directly compared to the bow-force limits found in an earlier empirical study using a bowing machine. 15 Bowing strategies for producing different dynamic levels will be analyzed dependent on note duration, shedding further light on the trade-off between bow velocity and bow-bridge distance in setting ͑or changing͒ the dynamic level, as suggested by Askenfelt. 9 Further, individual patterns in the ranges and variation of bowing parameters will be identified and compared to the common strategies.…”

Section: B Aims Of the Studymentioning

confidence: 99%

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The player and the bowed string: Coordination of bowing parameters in violin and viola performance

Schoonderwaldt

2009

The Journal of the Acoustical Society of America

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An experiment was conducted with four violin and viola players, measuring their bowing performance using an optical motion capture system and sensors on the bow. The measurements allowed for a detailed analysis of the use and coordination of the main bowing parameters bow velocity, bow force, and bow-bridge distance. An analysis of bowing strategies in detache playing of notes of three durations (0.2, 2, and 4 s) at three dynamic levels (pp, mf, and f) on all four strings is presented, focusing on the "steady" part of the notes. The results revealed clear trends in the coordinated variations of the bowing parameters depending on the constraints of the task, reflecting a common behavior as well as individual strategies. Furthermore, there were clear indications that the players adapted the bowing parameters to the physical properties of the string and the instrument, respecting the limits of the playable control parameter space.

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Section: A Sustained Notesmentioning

confidence: 86%

Section: A Sustained Notesmentioning

confidence: 92%

Section: Coordination Of Bowing Parameters In the Schelleng Diagrammentioning

confidence: 99%

Section: B Aims Of the Studymentioning

confidence: 99%

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The player and the bowed string: Coordination of bowing parameters in violin and viola performance

Schoonderwaldt

2009

The Journal of the Acoustical Society of America

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“…The acquisition of musical gestures and particularly of instrumental controls from a musical performance is a field of increasing interest with applications in acoustics (Schoonderwaldt et al, 2008), music pedagogy (Visentin et al, 2008), automatic music generation (Erkut et al, 2000;Maestre et al, 2010;Pérez-Carrillo et al, 2012), augmented performances (Bevilacqua et al, 2011; Proc. of the 11th International Symposium on CMMR, Plymouth, UK, June 16-19, 2015 Wanderley andDepalle, 2004) or performance transcription (Zhang and Wang, 2009) among others.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Guitar Fingering and Plucking Controls Based on Multimodal Analysis of Motion, Audio and Musical Score

Carrillo

Arcos

Wanderley

2016

Lecture Notes in Computer Science

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Abstract. This work presents a method for the extraction of instrumental controls during guitar performances. The method is based on the analysis of multimodal data consisting of a combination of motion capture, audio analysis and musical score. High speed video cameras based on marker identification are used to track the position of finger bones and articulations and audio is recorded with a transducer measuring vibration on the guitar body. The extracted parameters are divided into left hand controls, i.e. fingering (which string and fret is pressed with a left hand finger) and right hand controls, i.e. the plucked string, the plucking finger and the characteristics of the pluck (position, velocity and angles with respect to the string). Controls are estimated based on probability functions of low level features, namely, the plucking instants (i.e. note onsets), the pitch and the distances of the fingers (both hands) to strings and frets. Note onsets are detected via audio analysis, the pitch is extracted from the score and distances are computed from 3D Euclidean Geometry. Results show that by combination of multimodal information, it is possible to estimate such a comprehensive set of control features, with special high performance for the fingering and plucked string estimation. Regarding the plucking finger and the pluck characteristics, their accuracy gets lower but improvements are foreseen including a hand model and the use of high-speed cameras for calibration and evaluation.

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Bows, Strings, and Bowing

Guettler

2010

The Science of String Instruments

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An Empirical Investigation of Bow-Force Limits in the Schelleng Diagram

Cited by 21 publications

References 9 publications

The player and the bowed string: Coordination of bowing parameters in violin and viola performance

The player and the bowed string: Coordination of bowing parameters in violin and viola performance

Estimation of Guitar Fingering and Plucking Controls Based on Multimodal Analysis of Motion, Audio and Musical Score

Bows, Strings, and Bowing

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