AI meets music history: Viennese opera scores reinterpreted
Project Focus
This project is situated within the USTP's specialized research area of computer-aided manuscript analysis and builds upon two successful preliminary projects analyzing medieval manuscripts. While earlier work focused primarily on urban contexts, the current focus is on opera scores created at the Viennese court—an area that has received little systematic research to date.
Markus Seidl (https://icmt.ustp.at/team/markus-seidl) is a research partner working closely with project leader Martin Eybl (mdw – University of Music and Performing Arts Vienna, https://www.mdw.ac.at/imi/martin_eybl/), a leading expert in Viennese opera and copyist research, who has already examined large quantities of scores in two previous projects.
Aims and Methodology
Three key objectives are at the heart of this project:
- Identification and differentiation of copyists using computer vision and machine learning
- Dating undated manuscripts, including through the analysis of paper types used
- Investigation of the materiality of music manuscripts (paper, staff lines, binding techniques, collaborations between copyists)
To achieve this, image processing, optical music recognition, and AI methods are combined in a novel way.
Added Value
Computer-aided analysis enables faster and more precise classification of large manuscript collections. Differences in writing style become numerically comparable, allowing conclusions to be drawn about the experience and working methods of individual copyists. This opens up a new, data-driven approach to 18th-century music history.
Project Partners
- mdw – University of Music and Performing Arts Vienna
- USTP – St. Pölten
Funding Agency
Contact: Markus Seidl (Academic Director Creative Computing)
- markus.seidl@fhstp.ac.at