The Art of Teaching Computers: The SIMSSA Optical Music Recognition Workflow System
Ichiro Fujinaga, Gabriel Vigliensoni · 2019
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/teachers 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. In this environment, the humans are learning how to teach the machine more effectively.