The ACDH has established a scholarly-technical collaboration with the University of Alicante (Spain). The aim is to develop an infrastructure for Optical Music Recognition (OMR) for late medieval manuscripts and early modern prints of choir books containing plainchant (monophonic chant).

In this context, OMR refers to the automated, AI-assisted recognition and digital transcription of musical notation from image sources. Whereas traditional approaches worked only with limited success, contemporary deep-learning methods open new pathways, especially for complex historical notational systems..

The project will create tools for data annotation and curation, for training specialized models, and for content-based searching within transcribed materials. The collaboration combines the proven expertise of the Alicante team under Jorge Calvo Zaragoza’s leadership and chant scholar and AI expert Robert Klugseder with the resources of the ACDH.

The project focuses on Austrian chant sources and develops innovative software solutions for music research and digital editions. A central innovation is the provision of trained models directly in web browsers. This makes inference possible without powerful servers and creates low-barrier access. Plans include a freely available open-source tool for historical OMR as well as an online playground where researchers can test the tools. The models developed in the project will be made available to the scientific community.