In a recent study, members of the
Music and Machine Learning Lab of the Music Technology Group (MTG) at the
Department of Information and Communication Technologies (DTIC) of UPF, apply
artificial intelligence to the automatic classification of violin bow gestures
according to the performer’s movement. Researchers recorded movement and audio
data corresponding to seven representative bow techniques (Détaché, Martelé,
Spiccato, Ricochet, Sautillé, Staccato and Bariolage) performed by a
professional violinist. They obtained information about the inertial motion
from the right forearm and we synchronized it with the audio recordings.
The data used in this study are
available in an online public repository. After extracting the characteristics
of the information concerning movement and audio, the researchers trained a
system to automatically identify the different bow techniques used in playing
the violin. The model can determine the different techniques studied to more
than 94% accuracy. The results enable applying this work to a practical
learning scenario, in which students of violin can benefit from the feedback
provided by the system in real time. This study was conducted within the
framework of the TELMI (Technology Enhanced Learning Performance of Musical
Instrument) project.
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