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TELMI: Technology-Enhanced Learning of Music Instrument Performance.

The TELMI project addressing the challenges of music instrument learning by developing technologies to enhance musical learning. Using the violin as a case study, we have designed a system that embraces both traditional methods of violin instruction and modern cognitive research on how people gain expertise and learn skills efficiently and effectively. At the heart of the system are the groundbreaking advancements in audio and motion-capture analysis, and artificial intelligence techniques developed by the Pompeu Fabra University and the University of Genoa, and a solid pedagogical framework developed by the Royal College of Music, London

TELMI proposes a unified system that can be tailored to a wide range of musicians, experience levels, and learning situations. It will help musicians make the most of their time in lessons and practice, reduce injury and inefficiency, expand their access to communities of musical knowledge, and become better performers.


Rafael Ramírez

Dr. Rafael Ramirez is Tenured Associate Professor and Leader of the Music and Machine Learning Lab at the Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona. He obtained his BSc in Mathematics form the National Autonomous University of Mexico, his MSc in Artificial Intelligence and PhD in Computer Science from the University of Bristol, UK. He studied Classical Violin and Guitar at the National School of Music in Mexico, he has performed thoroughly in Europe, America and Asia. For five years, Dr. Ramirez was Lecturer in the National University of Singapore, Singapore. His current research interests include music technology, music therapy, artificial intelligence, neuroscience and their application to music learning, health and well-being. In particular, he has conducted research on modeling music listening, playing and learning using machine learning techniques, as well as on the impact of music as a therapeutic tool in autism, emotional disorders, palliative care, cerebral palsy, and stroke. He has published more than 120 research articles in peer-reviewed international Journals and Conferences, and acted as guest-editor of several special issues focused on music and artificial intelligence.