Title:
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Enhancing music learning with smart technologies
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Author:
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Ramírez, Rafael,1966-; Canepa, Corrado; Ghisio, Simone; Kolykhalova, Ksenia; Mancini, Maurizio; Volta, Erica; Volpe, Gualtiero; Giraldo, Sergio; Mayor, Oscar; Perez, Alfonso; Waddell, George; Williamon, Aaron
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Abstract:
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Comunicació presentada a: 5th International Conference on Movement and Computing, celebrat del 28 al 30 de juny de 2018 a Gènova, Itàlia. |
Abstract:
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Learning to play a musical instrument is a difficult task, requiring the development of sophisticated
skills. Nowadays, such a learning process is mostly based on the master-apprentice model. Technologies
are rarely employed and are usually restricted to audio and video recording and playback. The TELMI
(Technology Enhanced Learning of Musical Instrument Performance) Project seeks to design and
implement new interaction paradigms for music learning and training based on state-of-the-art
multimodal (audio, image, video, and motion) technologies.
Figure 1: Analysis of coordination, applying RecurrenceQuantification Analysis to
the kinetic energy of the right wrist.
Figure 2: A sample screen-shot of the intonation feedback on Piano Roll Mode.
Figure 3: A sample screen-shot of the intonation feedback on Score View Mode.
The project focuses on the violin as a case study. This practice work is intended as demo, showing to
MOCO attendants the results the project obtained along two years of work. The demo simulates a setup at a higher education music institution, where attendants with any level of previous violin experience
(and even with no experience at all) are invited to try the technologies themselves, performing basic
tests of violin skill and pre-defined exercises under the guidance of the researchers involved in the
project. |
Subject(s):
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-Violin -Multimodal interactive systems -Technology-enhanced learning -Music performance |
Rights:
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© ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 5th International Conference on Movement and Computing. http://doi.acm.org/10.1145/3212721.3212886 |
Document type:
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Conference Object Article - Accepted version |
Published by:
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ACM Association for Computer Machinery
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