Counterpoint error-detection tools for optical music recognition of Renaissance polyphonic music
Channel: Martha Thomae
Date: 2022-12-05

Four-minute video summary of my ISMIR 2022 paper. 

In this paper, we present a music information retrieval (MIR) pipeline to aid musicologists in making editions of mensural music sources. We designed this pipeline by improving existing MIR tools and allowing for their interoperability rather than implementing a new monolithic tool. These MIR tools include technologies such as optical music recognition (OMR), automatic voice alignment for mensural notation, editorial correction software, and computational counterpoint error detection. To ease the editorial correction process necessary to obtain correctly lined up scores, we evaluate whether the use of counterpointerror-detection tools makes the correction process more efficient. While this idea has been discussed before, this paper presents the first attempt at implementing it. The results confirm that marking illegal dissonances in the score following the rules of Renaissance counterpoint makes the process of editorial correction of scribal errors in Renaissance music more efficient by reducing the time taken and improving the accuracy of such corrections. Moreover, it also allowed us to catch OMR errors that had passed through undetected at a previous step of the pipeline. This paper is part of a larger project to preserve and increase access to a set of Guatemalan polyphonic choirbooks through digital images and symbolic scores.