List of results published directly linked with the projects co-funded by the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Program (MDM-2015-0502).

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Back Dalmazzo D, Ramirez R. Air violin: a machine learning approach to fingering gesture recognition. MIE 2017- Proceedings of the 1st ACM SIGCHI International Workshop on Multimodal Interaction for Education

Dalmazzo D, Ramirez R. Air violin: a machine learning approach to fingering gesture recognition. MIE 2017- Proceedings of the 1st ACM SIGCHI International Workshop on Multimodal Interaction for Education

We train and evaluate two machine learning models for predicting fingering in violin performances using motion and EMG sensors integrated in the Myo device. Our aim is twofold: first, provide a fingering recognition model in the context of a gamification virtual violin application where we measure both right hand (i.e. bow) and left hand (i.e. fingering) gestures, and second, implement a tracking system for a computer assisted pedagogical tool for self-regulated learners in high-level music education. Our approach is based on the principle of mapping-by-demonstration in which the model is trained by the performer. We evaluated a model based on Decision Trees and compared it with a Hidden Markovian Model.

Version in Zenodo: http://doi.org/10.5281/zenodo.1193758

Link: http://st.sigchi.org/publications/toc/mie-2017.html

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