Journal articles on the topic 'Violin Bowing'

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1

Hall, Cordelia, and John T. O'Donnell. "Regular Expressions as Violin Bowing Patterns." Computer Music Journal 36, no. 2 (June 2012): 74–84. http://dx.doi.org/10.1162/comj_a_00120.

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String players spend a significant amount of practice time creating and learning bowings. These may be indicated in the music using up-bow and down-bow symbols, but those traditional notations do not capture the complex bowing patterns that are latent within the music. Regular expressions, a mathematical notation for a simple class of formal languages, can describe precisely the bowing patterns that commonly arise in string music. A software tool based on regular expressions enables performers to search for passages that can be handled with similar bowings, and to edit them consistently. A computer-based music editor incorporating bowing patterns has been implemented, using Lilypond to typeset the music. Our approach has been evaluated by using the editor to study ten movements from six violin sonatas by W. A. Mozart. Our experience shows that the editor is successful at finding passages and inserting bowings; that relatively complex patterns occur a number of times; and that the bowings can be inserted automatically and consistently.
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2

Sun, Shih-Wei, Bao-Yun Liu, and Pao-Chi Chang. "Deep Learning-Based Violin Bowing Action Recognition." Sensors 20, no. 20 (October 9, 2020): 5732. http://dx.doi.org/10.3390/s20205732.

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We propose a violin bowing action recognition system that can accurately recognize distinct bowing actions in classical violin performance. This system can recognize bowing actions by analyzing signals from a depth camera and from inertial sensors that are worn by a violinist. The contribution of this study is threefold: (1) a dataset comprising violin bowing actions was constructed from data captured by a depth camera and multiple inertial sensors; (2) data augmentation was achieved for depth-frame data through rotation in three-dimensional world coordinates and for inertial sensing data through yaw, pitch, and roll angle transformations; and, (3) bowing action classifiers were trained using different modalities, to compensate for the strengths and weaknesses of each modality, based on deep learning methods with a decision-level fusion process. In experiments, large external motions and subtle local motions produced from violin bow manipulations were both accurately recognized by the proposed system (average accuracy > 80%).
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3

Mahmudin, Mohammad. "ANALISIS TEKNIK PERMAINAN VIOLIN II PADA LAGU CONCERTO FOR TWO VIOLINS, 1st MOVEMENT KARYA J.S. BACH." Repertoar Journal 2, no. 2 (July 9, 2022): 295–311. http://dx.doi.org/10.26740/rj.v2n2.p295-311.

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Abstrak: Penelitian ini membahas tentang teknik permainan violin yaitu teknik bowing dan teknik fingering lagu Concerto For Two Violins, 1st Movement karya J.S. Bach. Penelitian ini bertujuan untuk mendeskripsikan teknik permainan violin II pada Lagu Concerto For Two Violins, 1st Movement karya J.S. Bach. Metode yang digunakan pada penelitian ini adalah metode penelitian kualitatif deskriptif. Data yang diperoleh dalam penelitian ini melalui observasi, wawancara, dan dokumentasi. Teknik analisis data yang digunakan adalah reduksi data, penyajian data, dan kesimpulan data. Sementara itu, terdapat uji keabsahan data dengan teknik triangulasi. Hasil penelitian menunjukkan bahwa teknik permainan yang digunakan violin II pada lagu Concerto For Two Violins, 1st Movement karya J.S. Bach adalah teknik staccato, legato, legatura, trill, tenutto, vobrato dan accent. Sementara itu, terdapat tanda ekspresi dan dinamika diantaranya adalah diminuendo, poco dim, ritardo, vermata, forte (f), mezzo forte (ff), crescendo (<), decrescendo (>), piano (p), pianissimo (pp), dan mezzo piano (mp).
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4

Provenzale, Cecilia, Nicola Di Stefano, Alessia Noccaro, and Fabrizio Taffoni. "Assessing the Bowing Technique in Violin Beginners Using MIMU and Optical Proximity Sensors: A Feasibility Study." Sensors 21, no. 17 (August 29, 2021): 5817. http://dx.doi.org/10.3390/s21175817.

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Bowing is the fundamental motor action responsible for sound production in violin playing. A lot of effort is required to control such a complex technique, especially at the beginning of violin training, also due to a lack of quantitative assessments of bowing movements. Here, we present magneto-inertial measurement units (MIMUs) and an optical sensor interface for the real-time monitoring of the fundamental parameters of bowing. Two MIMUs and a sound recorder were used to estimate the bow orientation and acquire sounds. An optical motion capture system was used as the gold standard for comparison. Four optical sensors positioned on the bow stick measured the stick–hair distance. During a pilot test, a musician was asked to perform strokes using different sections of the bow at different paces. Distance data were used to train two classifiers, a linear discriminant (LD) classifier and a decision tree (DT) classifier, to estimate the bow section used. The DT classifier reached the best classification accuracy (94.2%). Larger data analysis on nine violin beginners showed that the orientation error was less than 2°; the bow tilt correlated with the audio information (r134=−0.973, 95% CI −0.981,−0.962, p<0.001). The results confirmed that the interface provides reliable information on the bowing technique that might improve the learning performance of violin beginners.
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5

Brown, Clive. "Bowing Styles, Vibrato and Portamento in Nineteenth-Century Violin Playing." Journal of the Royal Musical Association 113, no. 1 (1988): 97–128. http://dx.doi.org/10.1093/jrma/113.1.97.

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There are many aspects of nineteenth-century violin playing that have received little attention from scholars. The subject is a vast and complicated one, far beyond the scope of a short article to treat adequately, but there are a number of important areas in which problems have not even been recognized, let alone investigated. For instance, the most substantial recent work on this subject, Robin Stowell's Violin Technique and Performance Practice in the Late Eighteenth and Early Nineteenth Centuries (Cambridge, 1985), provides a useful digest of what the major violin methods of the period say, but because it is mainly confined to these sources, ignoring for the most part journalism and other contemporary accounts, and because it has a rather artificial terminal date of 1840, it fails to illuminate major underlying patterns of continuity and change in nineteenth-century violin playing. It may be valuable, therefore, to put forward a few ideas and suggest a few fruitful lines of enquiry which have until now remained largely unconsidered.
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6

Adzkia, Sagaf, and Alya Sabina Muntasya. "Variasi Bowing Etudes Ou Caprices No. 2 Rodolphe Kreutzer Sebagai Strategi Pembentukan Teknik Tangan Kanan Pada Pemain Violin." Virtuoso: Jurnal Pengkajian dan Penciptaan Musik 5, no. 2 (November 27, 2022): 96–103. http://dx.doi.org/10.26740/vt.v5n2.p96-103.

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Violin players are required to have balanced technical skills not only with the left hand (finger operation on the strings), but also the role of the right hand (playing the bow). Qualifications that emphasize exercises that focus on right-hand skills are in fact often under-appreciated. This research proposal presents a study-based violin learning strategy that emphasizes right hand skills through bowing variation treatment, which is applied to Rodolphe Kreutzer's Etudes Ou Caprices No. 2. The focus of this research is the music education study program, ISI Yogyakarta. This study uses a qualitative method with a musicological approach. The stages that were passed in this research were through the process of literature study, observation, interviews, and analysis. The results of this study are: the emergence of eight variations of bowing which was applied to Etudes Ou Caprices no.2 Rodolphe Kreutzer; the treatment applied is useful in improving the right hand technique and the differentiating specifications between each bowing technique; through continuous practice of bowing variation techniques can make students responsive in reading notation symbols, especially on the diversity of right-handed techniques; treatment of variations of bowing detache, staccato, spiccato, legato, and their variations can be easily applied to the repertoire/songs being studied to support interpretation.
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7

SHIBUYA, Koji, and Shigeki SUGANO. "Analysis of Bowing Motion in Violin Playing." Japanese journal of ergonomics 32, Supplement (1996): 96–97. http://dx.doi.org/10.5100/jje.32.supplement_96.

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8

Hall, Cordelia V., and John T. O’Donnell. "Calibrating a bowing checker for violin students." Journal of Music, Technology and Education 3, no. 2 (April 19, 2011): 125–39. http://dx.doi.org/10.1386/jmte.3.2-3.125_1.

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9

Schoonderwaldt, Erwin, and Eckart Altenmüller. "Coordination in Fast Repetitive Violin-Bowing Patterns." PLoS ONE 9, no. 9 (September 10, 2014): e106615. http://dx.doi.org/10.1371/journal.pone.0106615.

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10

Bishop, Laura, and Werner Goebl. "Beating time: How ensemble musicians’ cueing gestures communicate beat position and tempo." Psychology of Music 46, no. 1 (April 27, 2017): 84–106. http://dx.doi.org/10.1177/0305735617702971.

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Ensemble musicians typically exchange visual cues to coordinate piece entrances. “Cueing-in” gestures indicate when to begin playing and at what tempo. This study investigated how timing information is encoded in musicians’ cueing-in gestures. Gesture acceleration patterns were expected to indicate beat position, while gesture periodicity, duration, and peak gesture velocity were expected to indicate tempo. Same-instrument ensembles (e.g., piano–piano) were expected to synchronize more successfully than mixed-instrument ensembles (e.g., piano–violin). Duos performed short passages as their head and (for violinists) bowing hand movements were tracked with accelerometers and Kinect sensors. Performers alternated between leader/follower roles; leaders heard a tempo via headphones and cued their partner in nonverbally. Violin duos synchronized more successfully than either piano duos or piano–violin duos, possibly because violinists were more experienced in ensemble playing than pianists. Peak acceleration indicated beat position in leaders’ head-nodding gestures. Gesture duration and periodicity in leaders’ head and bowing hand gestures indicated tempo. The results show that the spatio-temporal characteristics of cueing-in gestures guide beat perception, enabling synchronization with visual gestures that follow a range of spatial trajectories.
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11

Askenfelt, Anders. "Measurement of the bowing parameters in violin playing." Journal of the Acoustical Society of America 84, S1 (November 1988): S163. http://dx.doi.org/10.1121/1.2025927.

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12

Baader, Andreas P., Oleg Kazennikov, and Mario Wiesendanger. "Coordination of bowing and fingering in violin playing." Cognitive Brain Research 23, no. 2-3 (May 2005): 436–43. http://dx.doi.org/10.1016/j.cogbrainres.2004.11.008.

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13

Ye, Bang Yan, Jian Ping Liu, Cheng Zhong Zhang, X. Z. Zhao, S. S. Liang, and J. Y. Niu. "Vibration Characteristic of Violin Bowstring and Experimental Research on Helmholtz Motion of String." Key Engineering Materials 621 (August 2014): 707–11. http://dx.doi.org/10.4028/www.scientific.net/kem.621.707.

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The sound source of violin is string vibration. By the stick–slip friction action between bow and string of violin, string and bridge form a complicated vibration system. The interaction mechanism of bowstring is very intricacy. In this paper, through theoretical analysis and experiment, the vibration behavior of violin string is investigated. We measured the vibration images of bowing and plucking violin string on a high-speed photography optical platform and got two different character of string vibration, including vibration displacement, velocity and space trajectory of the mark point on string. By comparing the displacement curves of the different points among on string, the variety of the ratio of positive process time to negative one of vibration sawtooth waveform are studied, and also the formation process of string vibration enveloping curve. On this basis, the Helmholtz motion of string vibration which is presented at 1862 is studied.
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14

SHIBUYA, Koji, Shigeki SUGANO, and Ichiro KATO. "Skill-analysis of the bowing motion in violin playing." Japanese journal of ergonomics 30, no. 6 (1994): 395–403. http://dx.doi.org/10.5100/jje.30.395.

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15

Maestre, Esteban. "Synthesis of bowing controls applied to violin sound generation." Journal of the Acoustical Society of America 130, no. 4 (October 2011): 2431. http://dx.doi.org/10.1121/1.3654747.

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16

Shibuya, Koji, Hironori Ideguchi, and Katsunari Ikushima. "Volume Control by Adjusting Wrist Moment of Violin-Playing Robot." International Journal of Synthetic Emotions 3, no. 2 (July 2012): 31–47. http://dx.doi.org/10.4018/jse.2012070102.

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This paper introduces the details of the anthropomorphic violin-playing robot built in the authors’ laboratory and an algorithm for controlling the sound volume by adjusting its wrist moment. Investigating the relationship between such sound parameters as sound volume and human impressions is an important research field in Kansei Engineering, which is a growing research field in Japan. They focused on the violin and built a violin-playing robot with two 7 DOF arms for bowing and fingering. Then they constructed an algorithm to adjust the wrist moment to control the sound volume. Based on the result of the experiments, the authors concluded that the moment-based algorithm works well to successfully control the sound volume. Finally, they analyzed the sound spectrum of the produced sounds of different wrist moment, and concluded that there is a possibility for the controlling sound spectrum, which affects human impressions.
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17

Lee, André, and Eckart Altenmüller. "Primary Task-specific Bowing Tremor: An Entity of its Own?" Medical Problems of Performing Artists 27, no. 4 (December 1, 2012): 224–26. http://dx.doi.org/10.21091/mppa.2012.4041.

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A professional violinist in his early 60s, playing in a prestigious German orchestra for more than 20 years, presented to our institute because of a task-induced tremor in his right arm when playing the violin. We describe the phenomenology of this tremor and its treatment options and compare it to findings in primary writing tremor (PWT). We then discuss whether primary bowing tremor is an entity of its own (similar to PWT) and propose hypotheses that would derive from such a definition.
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18

Alar, Hernan S., Ramil O. Mamaril, Lex P. Villegas, and Jhon Roe D. Cabarrubias. "Audio classification of violin bowing techniques: An aid for beginners." Machine Learning with Applications 4 (June 2021): 100028. http://dx.doi.org/10.1016/j.mlwa.2021.100028.

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19

Abbas Al-Sudani, Mustafa. "THE ROLE OF GENERAL VIOLIN BOWING RULES WITHIN IRAQI PLAYERS." Route Educational and Social Science Journal 8, no. 64 (January 1, 2021): 47–65. http://dx.doi.org/10.17121/ressjournal.3021.

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20

Schoonderwaldt, Erwin, Matthias Demoucron, Eckart Altenmüller, and Marc Leman. "Perception and production of complex bowing movements in violin performance." Journal of the Acoustical Society of America 133, no. 5 (May 2013): 3270. http://dx.doi.org/10.1121/1.4805312.

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21

Maestre, Esteban, Merlijn Blaauw, Jordi Bonada, Enric Guaus, and Alfonso Perez. "Statistical Modeling of Bowing Control Applied to Violin Sound Synthesis." IEEE Transactions on Audio, Speech, and Language Processing 18, no. 4 (May 2010): 855–71. http://dx.doi.org/10.1109/tasl.2010.2040783.

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22

Shan, Gongbing, Peter Visentin, Luke Wooldridge, Changdong Wang, and Dennis Connolly. "A Frequency-Based Characterization of Spiccato Bowing in Violin Performance." Perceptual and Motor Skills 105, no. 3_suppl (December 2007): 1027–51. http://dx.doi.org/10.2466/pms.105.4.1027-1051.

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23

VISENTIN, PETER. "A FREQUENCY-BASED CHARACTERIZATION OF SPICCATO BOWING IN VIOLIN PERFORMANCE." Perceptual and Motor Skills 105, no. 7 (2007): 1027. http://dx.doi.org/10.2466/pms.105.7.1027-1051.

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24

Roh, YuJi, and Young H. Kim. "Dependence of sound characteristics on the bowing position in a violin." Journal of the Korean Physical Society 65, no. 11 (December 2014): 1853–57. http://dx.doi.org/10.3938/jkps.65.1853.

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25

SHIBUYA, Koji, and Shigeki SUGANO. "SENSORY TEST RELATING TIMBRE WORDS TO BOWING PARAMETERS IN VIOLIN PLAYING." Biomechanisms 15 (2000): 153–64. http://dx.doi.org/10.3951/biomechanisms.15.153.

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26

Maestre, Esteban, and Rafael Ramírez. "An approach to predicting bowing control parameter contours in violin performance." Intelligent Data Analysis 14, no. 5 (September 10, 2010): 587–99. http://dx.doi.org/10.3233/ida-2010-0441.

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27

van der Linden, Janet, Erwin Schoonderwaldt, Jon Bird, and Rose Johnson. "MusicJacket—Combining Motion Capture and Vibrotactile Feedback to Teach Violin Bowing." IEEE Transactions on Instrumentation and Measurement 60, no. 1 (January 2011): 104–13. http://dx.doi.org/10.1109/tim.2010.2065770.

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28

Bernad Julianto, Sih Pungki. "ANALISIS TEKNIK PERMAINAN VIOLIN PADA CONCERTO IN A MINOR 1ST MOVEMENT KARYA ANTONIO VIVALDI." Repertoar Journal 2, no. 2 (July 9, 2022): 312–22. http://dx.doi.org/10.26740/rj.v2n2.p312-322.

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Concerto in A Minor merupakan lagu yang diciptakan oleh Antonio Vivaldi, yang memiliki 3 bagian (movement) dan dimainkan dengan format solo violin dengan iringan orkestra. Pada penelitian ini, peneliti fokus pada bagian yang pertama. Concerto in A minor 1st movement menggunakan nada dasar A Minor dan terdapat modulasi menuju tangga nada E Minor dengan tempo Allegro (cepat). Adapun tujuan dari penelitian ini ialah untuk mendeskripsikan teknik permainan violin yang meliputi teknik bowing dan teknik penjarian pada lagu Concerto in A Minor 1st movement karya Antonio Vivaldi. Metode penelitian yang digunakan yaitu penelitian kualitatif deskriptif. Objek dalam penelitian ini adalah lagu Concerto in A Minor 1st movement karya Antonio Vivaldi. Teknik pengumpulan data dilakukan dengan cara observasi, wawancara, dan dokumentasi. Hasil penelitian ini menunjukan bahwa Concerto in A Minor 1st Movement karya Antonio Vivaldi mempunyai beragam teknik permainan yaitu Staccato, Legato, Accent, Tenuto, dan Martellato serta penggunaan posisi penjarian 1, 2, dan 3. Sementara itu, Concerto in A Minor 1st Movement karya Antonio Vivaldi mempunyai dinamika yaitu piannisimo, piano, messoforte, dan forte. Komposisi lagu ini menggunakan bentuk musik Rittornello Form. Kata Kunci : Teknik Permainan, Violin, Concerto
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29

Yagisan, Nihan, Hakan Karabork, Ayhan Goktepe, and Nazim Karalezli. "Evaluation of Three-Dimensional Motion Analysis of the Upper Right Limb Movements in the Bowing Arm of Violinists Through a Digital Photogrammetric Method." Medical Problems of Performing Artists 24, no. 4 (December 1, 2009): 181–84. http://dx.doi.org/10.21091/mppa.2009.4036.

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Violin is one of the most widely taught string instruments in the world. The positions of the right upper arm, elbow, and wrist and the vertical inclinations of the arm and forearm differ among violin players. The objective of this study was to measure the angular changes in the wrist and elbow joints, as well as the vertical inclinations of the arm, forearm, and hand, which are active in basic bow drives in violin playing, by using digital photogrammetric methods. In this way, we could determine the angular changes of the joints during bow drives, allowing us to incorporate this information into teaching proper bow techniques as well as preventing possible problems due to excessive force. This study involved nine male university violin players. Certain anatomic areas were marked on the players for measurement. The wrist and elbow joints of the right upper extremity were filmed on a calibrated test field using a metric camera, and images were transferred to the computer for photogrammetric evaluation using Pictran software (Technet GmbH, Germany). The angles of the elbow and wrist as well as the vertical inclinations of the arm, forearm, and hand of the right arm were ascertained from these marks on the photographs. The study showed that there are significant interindividual differences in the angular changes and inclinations on the E string and in the vertical inclinations on all strings among the different players.
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30

Satria Yogaswara, Adre. "ANALISIS BENTUK MUSIK DAN TEKNIK PERMAINAN VIOLIN PADA PRAELUDIUM AND ALLEGRO KARYA FRITZ KREISLER." Repertoar Journal 2, no. 2 (April 12, 2022): 231–47. http://dx.doi.org/10.26740/rj.v2n2.p231-247.

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Penelitian ini bertujuan untuk mendeskripsikan bentuk musik dan struktur, serta mendeskripsikan teknik permainan violin yang meliputi teknik bowing dan penjarian (fingering) pada Praeludium and Allegro karya Fritz Kreisler. Penelitian ini menggunakan metode penelitian deskriptif kualitatif. Objek dalam penelitian ini adalah partitur Praeludium and Allegro karya Fritz Kreisler. Data penelitian diperoleh melalui observasi, wawancara, studi pustaka, dan studi dokumentasi. Teknik analisis data yang digunakan adalah reduksi data, penyajian data dan kesimpulan data. Hasil dan pembahasan dalam penelitian ini menunjukkan bahwa Praeludium and Allegro karya Fritz Kreisler terdiri dari dua movement. Movement pertama yaitu dalam tempo Allegro yang menggunakan bentuk musik praeludium atau prelude yang memiliki struktur A – B – A’. Movement kedua menggunakan bentuk rondo dua sisipan yaitu A – A’ – B – C – A’’ – D – E. Teknik permainan yang digunakan dalam komposisi ini adalah accent, detache, legato, spicato, multiple stop, dan tril, sedangkan posisi penjarian yang digunakan adalah dari posisi 1st hingga posisi 10th. Kata Kunci: Prelude, Rondo, Bentuk Musik, Teknik Permainan Violin
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31

SHIBUYA, Koji, and Shigeki SUGANO. "Relating KANSEI information to bowing parameters for the planning of violin playing." Japanese journal of ergonomics 33, Supplement (1997): 392–93. http://dx.doi.org/10.5100/jje.33.supplement_392.

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32

SHIBUYA, Koji, Koshi FUKATSU, and Shigenori KOMATSU. "Influences of timbre on right arm motion in bowing of violin playing." Journal of the Society of Biomechanisms 28, no. 3 (2004): 146–54. http://dx.doi.org/10.3951/sobim.28.146.

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33

SATO, Yosuke, and Shigeru AOMURA. "B207 Study on violin bowing machine which controls bow speed and pressure." Proceedings of the JSME Conference on Frontiers in Bioengineering 2008.19 (2008): 54–55. http://dx.doi.org/10.1299/jsmebiofro.2008.19.54.

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34

Schoonderwaldt, E., and M. Demoucron. "Extraction of bowing parameters from violin performance combining motion capture and sensors." Journal of the Acoustical Society of America 126, no. 5 (November 2009): 2695–708. http://dx.doi.org/10.1121/1.3227640.

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35

Chalko, T. J., and C. E. Williams. "Six degrees of freedom motion measurement with application to violin-bowing analysis." Experimental Mechanics 27, no. 4 (December 1987): 423–28. http://dx.doi.org/10.1007/bf02330317.

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36

MATSUDA, Syoji, Akira TAKAHARA, Koji SHIBUYA, and Taro IWAMOTO. "1A2-D09 Bowing Motion for Violin by 7 D.O.F Anthropomorphic Robot Arm." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2007 (2007): _1A2—D09_1—_1A2—D09_3. http://dx.doi.org/10.1299/jsmermd.2007._1a2-d09_1.

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37

Young, Diana. "A system for understanding violin bowing technique through measurement of physical dynamics." Journal of the Acoustical Society of America 119, no. 5 (May 2006): 3441. http://dx.doi.org/10.1121/1.4808874.

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38

Duprey, S., B. Michaud, and M. Begon. "Muscular activity variations of the right bowing arm of the violin player." Computer Methods in Biomechanics and Biomedical Engineering 20, sup1 (October 27, 2017): S71—S72. http://dx.doi.org/10.1080/10255842.2017.1382866.

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39

Sholehuddin, Ridho. "ANALISIS TEKNIK PERMAINAN VIOLIN CONCERTO IN A MINOR 2nd MOVEMENT KARYA A. VIVALDI." Repertoar Journal 2, no. 1 (November 10, 2021): 157–70. http://dx.doi.org/10.26740/rj.v2n1.p157-170.

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Penelitian ini berjudul Analisis Teknik Permainan Violin Concerto in A minor 2nd Movement Karya Antonio Vivaldi. Penelitian ini bertujuan untuk mendeskripsikan teknik permainan yang ada di dalam karya tersebut. Penelitian ini menggunakan metode penelitian kualitatif deskriptif. Karya ini terdapat 3 bagian yakni bagian 1, 2, dan 3 menggunakan tempo Allegro, Largo, dan Presto. Teknik bowing yang terdapat pada concerto in A minor 2nd Movement karya A. Vivaldi yaitu Legato, Tenuto, dan Trill. Sementara itu, teknik penjarian pada karya tersebut yaitu penggunaan posisi 1, 2, 3, 4, 5. Selanjutnya, penggunaan tanda ekspresi dalam karya ini antara lain Piano, Pianissimo, Forte, Mezzo forte, Ritardando, Crescendo, dan Decrescendo.
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40

Wolf, Edward, Dirk Möller, Nikolaus Ballenberger, Karsten Morisse, and Kristoff Zalpour. "Marker-Based Method for Analyzing the Three-Dimensional Upper Body Kinematics of Violinists and Violists: Development and Clinical Feasibility." Medical Problems of Performing Artists 34, no. 4 (December 1, 2019): 179–90. http://dx.doi.org/10.21091/mppa.2019.4029.

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AIMS: High string players (violin and viola) often suffer from musculoskeletal disorders. Although 3D motion analysis has proved helpful in diagnosing different musculoskeletal syndromes and identifying injurious movement patterns in violin and viola performance, more detailed analyses of upper body movement strategies and especially of the shoulder complex have not yet been recorded. The use of spherical surface markers on some anatomical landmarks is, however, inappropriate when an instrument is being played. The aim of this study was to develop and evaluate a novel marker-based method for analyzing upper body kinematics of high string players using conditions specific to violin and viola playing. METHODS: A custom upper body marker set was developed and a biomechanical model applied to 3D motion capture data of the pelvis, thorax, spine, head, and both upper limbs (scapula, upper arm, forearm, hand) of 12 professional violinists, to assess its clinical feasibility. FINDINGS: Lumbar and thoracic spine, thorax, neck, and left upper limb were quite static, while extensive motion occurred in the right upper limb. Most rotation angles showed a reasonable intersubject variability except for glenohumeral and wrist joints. Significant differences were observed between G- and D-string bowing, especially in the left wrist and right shoulder joints. INTERPRETATION: This study suggests that the proposed method is a valid tool for quantifying upper body movements in violin and viola performance. With the extended upper body model, it will improve understanding of the motor strategies adopted by high string players and may contribute to injury prevention, diagnosis, and treatment.
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41

Maestre, Esteban. "Analysis/synthesis of bowing control applied to violin sound rendering via physical models." Journal of the Acoustical Society of America 133, no. 5 (May 2013): 3271. http://dx.doi.org/10.1121/1.4805315.

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42

Perez-Carrillo, Alfonso. "Statistical models for the indirect acquisition of violin bowing controls from audio analysis." Journal of the Acoustical Society of America 140, no. 4 (October 2016): 3091. http://dx.doi.org/10.1121/1.4969634.

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43

MATSUI, Toshikazu, Nobutaka OI, and Yasunobu KIMURA. "Three-Joint Arm's Optimal Control Model for Simulating Human Arm's Violin-Bowing Movements." Proceedings of the Symposium on sports and human dynamics 2019 (2019): B—15. http://dx.doi.org/10.1299/jsmeshd.2019.b-15.

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44

Fujita, K., Y. Miyanishi, K. Shibuya, and T. Iwamoto. "The relationship between timbre and bowing parameters in phrase playing of violin playing." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 94. http://dx.doi.org/10.1299/jsmermd.2004.94_3.

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45

IKUSHIMA, Katsunari, and Koji SHIBUYA. "2P1-Q04 Design of Bowing-Machine for Revealing Relationship between Bowing and Sound Parameters in Violin Playing(Robots for Amusement and Entertainment)." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2013 (2013): _2P1—Q04_1—_2P1—Q04_2. http://dx.doi.org/10.1299/jsmermd.2013._2p1-q04_1.

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46

YABU, Hironoshin, Tkao ARATANI, and Koji SHIBUYA. "1A1-D05 An Algorithm for Motion Planning of Violin-playing Robot : Determining Bowing Direction and Three Bowing Parameters(Robots for Amusement and Entertainment)." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2014 (2014): _1A1—D05_1—_1A1—D05_2. http://dx.doi.org/10.1299/jsmermd.2014._1a1-d05_1.

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47

Schoonderwaldt, E. "On the Use of Skewness in Violin Bowing: Should the Bow be Straight or Not?" Acta Acustica united with Acustica 96, no. 4 (July 1, 2010): 593–602. http://dx.doi.org/10.3813/aaa.918314.

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48

Askenfelt, Anders. "Between the frog and the tip ‐ bowing gestures and bow‐string interaction in violin playing." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3656. http://dx.doi.org/10.1121/1.2934962.

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49

Schoonderwaldt, E. "The player and the bowed string: Coordination of bowing parameters in violin and viola performance." Journal of the Acoustical Society of America 126, no. 5 (November 2009): 2709–20. http://dx.doi.org/10.1121/1.3203209.

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D’Amato, Vincenzo, Erica Volta, Luca Oneto, Gualtiero Volpe, Antonio Camurri, and Davide Anguita. "Understanding Violin Players’ Skill Level Based on Motion Capture: a Data-Driven Perspective." Cognitive Computation 12, no. 6 (September 24, 2020): 1356–69. http://dx.doi.org/10.1007/s12559-020-09768-8.

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AbstractLearning to play and perform a music instrument is a complex cognitive task, requiring high conscious control and coordination of an impressive number of cognitive and sensorimotor skills. For professional violinists, there exists a physical connection with the instrument allowing the player to continuously manage the sound through sophisticated bowing techniques and fine hand movements. Hence, it is not surprising that great importance in violin training is given to right hand techniques, responsible for most of the sound produced. In this paper, our aim is to understand which motion features can be used to efficiently and effectively distinguish a professional performance from that of a student without exploiting sound-based features. We collected and made freely available a dataset consisting of motion capture recordings of different violinists with different skills performing different exercises covering different pedagogical and technical aspects. We then engineered peculiar features and trained a data-driven classifier to distinguish among two different levels of violinist experience, namely beginners and experts. In accordance with the hierarchy present in the dataset, we study two different scenarios: extrapolation with respect to different exercises and violinists. Furthermore, we study which features are the most predictive ones of the quality of a violinist to corroborate the significance of the results. The results, both in terms of accuracy and insight on the cognitive problem, support the proposal and support the use of the proposed technique as a support tool for students to monitor and enhance their home study and practice.
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