In many machine learning systems, it would be effective to create a pedagogical environment where both the machines and the humans can incrementally learn to solve problems through interaction and adaptation. We are designing an optical music recognition workflow system within the SIMSSA (Single Interface for Music Score Searching and Analysis) project, where human operators can intervene to correct and teach the system at certain stages in the optical music recognition process so that both parties can learn from the errors and, consequently, the overall performance is increased progressively as more music scores are processed.

About Ichiro Fujinaga

Ichiro Fujinaga is an Associate Professor of Music Technology in the Schulich School of Music, McGill University. He has Bachelor’s degrees in Music/Percussion and Mathematics from University of Alberta, and a Master’s degree in Music Theory and a PhD in Music Technology from McGill University. From 1993 to 2002, he was a faculty member of the Computer Music Department at the Peabody Conservatory of Music of the Johns Hopkins University. Returning to McGill in 2002, he became the Acting Director of the Center for Interdisciplinary Research in Music Media and Technology (CIRMMT) (2003–2004). He was appointed as the Chair of the Music Technology Area in the Department of Music Research four times as well as the Associate Dean (Research), Schulich School of Music (2016–2017).

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