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Development of a Comprehensive Cloud-Based Toolbox for Sheet Music Analysis

Subject Area Musicology
Term since 2025
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 555937418
 
New approaches to musical analysis, a core methodology of musicology and music theory, are increasingly leveraging the capabilities of computers, particularly in corpus analyses with diverse research questions and musical repertoires. This project aims to develop and evaluate a comprehensive and user-friendly open-source software toolbox for sheet music annotation, statistical analysis, visualization, and pattern search operations. Employing cutting-edge computer, internet, and cloud technologies, in particular Jupyter4NFDI, the toolbox is intended to be applicable and adaptable across a vast array of research issues of music analysis which are extensively discussed in current musicology and music theory research. The toolset will be designed to be user-friendly for music researchers, even those lacking programming expertise. It will incorporate state-of-the-art music data formats such as MusicXML and MEI, as well as data frame solutions. Sheet music datasets encompass optical music recognition (OMR) data from the musiconn.scoresearch project by the Bavarian State Library (mainly compositions from the 17th to 19th centuries) as well as public domain sheet music from early 20th-century composers. The project also aims to contribute to the further development of the MEI format and mei-friend, a renowned web-based tool for MEI editing. This will be achieved by extending the tool's functionality and adding new annotation options, including harmonic functions, microtonal notations, and metrically free notations. Throughout the project's duration, both the software tools and cloud infrastructure, as well as comprehensive open-access online documentation and tutorials for various use cases and research issues related to musical analysis and diverse sheet music corpora, will be developed. These resources will be tested, evaluated, and subsequently optimized in music analysis courses at the Institute for Musicology and the Center of Music Theory of the University of Music Franz Liszt Weimar, as well as in a public workshop. A final report will document the challenges and solutions encountered during the development of such technology. The resulting tools will be maintained by the University of Music Weimar beyond project runtime, so they can persistently continue to contribute to the growing field of computational music research.
DFG Programme Research data and software (Scientific Library Services and Information Systems)
 
 

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