Starting in September 2025, the CAMAT toolbox will be redeveloped and substantially extended within the research project A Comprehensive Cloud-Based Toolbox for Sheet Music Analysis.
You can follow the project’s progress, including alpha releases and datasets, on our GitHub project website: https://github.com/analyse-hfm-weimar

The goal of this project is to develop an open-source, Python-based toolkit for interactive sheet music analysis. Built on Verovio, mei-friend, and Jupyter—in particular via the cloud-based Jupyter4NFDI platform—the toolbox enables comprehensive exploration, annotation, visualization, and statistical analysis of symbolic music data as well as pattern-search methods for melodic, harmonic, rhythmic, and textural analysis. Supported formats include MEI, kern, and MusicXML, also supporting established parsers such as music21 and Partitura. The toolbox allows interactive score rendering and customizable corpus creation from validated OMR-based sources. Reproducible Jupyter workflows are combined with openly available datasets, in particular data derived from the musiconn project, including the Denkmäler der deutschen Tonkunst (Series I & II), as well as selected works from the early 20th century. By integrating and producing openly accessible corpora in MEI format, the project aims to lower barriers to computational music analysis and to foster the broader adoption of digital methods in musicology, music theory, and music pedagogy.

Project runtime: September 2025 until August 2028
Funded by the German Research Foundation (DFG), program Library and Information Services - E-Research Technologies (LIS) (PF 669/19-1)

Research team:

• Prof. Dr. Martin Pfleiderer (applicant)
• Dr. Egor Polyakov (scientific assistant)
• Pia Steuck (student assistant)

• Audio Analysis
• Sheet Music Analysis
• Sheet Music Database
• Software Installation
• Resources and Documentation
• The project

Courses on musical analysis are an integral part of both musicology courses and the training of music teachers and musicians at universities and conservatories. The goal of the fellowship project is to design, test, evaluate, and teach several flexibly applicable teaching modules on music analysis, with recourse to various computer-based analysis tools. The teaching modules are dedicated to computer-based annotation and visualization of musical texts and audio files, statistical analysis of music corpora, and search for musical patterns (melodies, rhythms etc.). They are intended to complement conventional analysis courses, have been and evaluated within several courses at the HfM Weimar, and will are publicly available to a wider circle of interested parties via this Internet platform.

Computers can be used as aids in the analysis of musical texts and recordings. Computer programs can be used to quickly and reliably

• visualize musical sequences and structures,
• statistically describe musical characteristics of the pieces in question (e.g. frequencies of pitches)
• and searched for specific patterns (e.g. melodic motifs).

This extends conventional approaches to analysis and opens up and explores new perspectives of musical analysis in musicology and music theory. On the one hand, the computer tools can be used to pursue specific analytical questions, and on the other hand, a playful approach to the tools and note files enables the discovery of unexpected relationships - which can then lead to new analytical questions.

The Teaching modules and tutorials are provided that introduce various possibilities of computer-assisted analysis of sheet music or audio files on the basis of music-analytical issues. Each teaching unit consists of a basic module (Basics Sheet Music or Basics Audio) and a specialization (Advanced). The teaching units can be used in self-study or within courses. The duration of the teaching units is approximately three sessions of 90-minutes, with additional preparation, homework and optional specializations.

All software used in the teaching units is freely accessible and license-free. Thus, the project follows the principle of open access - open access to publicly funded project results and independence from commercially oriented IT corporations.

The project Computergestützte Musikanalyse in der digitalen Hochschullehre (computer-aided music analysis within digital higher education) is located at the Institute of Musicology Weimar-Jena of the Franz Liszt University of Music Weimar. It was funded in 2021 by the Thuringian Ministry for Economy, Science and Digital Change and the Stifterverband. The project sees itself as a contribution to Computational Musicology or Digital Musicology within Digital Humanities. Further information about the project's objectives, staff etc. can be found on The project.

Feedback is welcome: analyse@hfm-weimar.de

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