Efficient optical music recognition validation using MIDI sequence data

Abstract

Despite advances in optical music recognition (OMR), resultant scores are rarely error-free. The power of these OMR systems to automatically generate searchable and editable digital representations of physical sheet music is lost in the tedious manual effort required to pinpoint and correct these errors post-OMR, or even to just confirm no errors exist. To streamline post-OMR error correction, I developed a corrector to automatically identify discrepancies between resultant OMR scores and corresponding Musical Instrument Digital Interface (MIDI) scores and then either automatically fix errors, or in ambiguous cases, notify the user to manually fix errors. This tool will be open source, so anyone can contribute to further improving the accuracy of OMR tools and expanding the amount of trusted digitized music.