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.