CATMuS Medieval: A Multilingual Large-Scale Cross-Century Dataset in Latin Script for Handwritten Text Recognition and Beyond

Thibault Clérice, Ariane Pinche, Malamatenia Vlachou-Efstathiou, Alix Chagué, Jean-Baptiste Camps, Matthias Gille Levenson, Olivier Brisville-Fertin, Federico Boschetti, Franz Fischer, Michael Gervers, Agnès Boutreux, Avery Manton, Simon Gabay, Patricia O'Connor, Wouter Haverals, Mike Kestemont, Caroline Vandyck, Benjamin Kiessling

Abstract: The surge in digitisation initiatives by Cultural Heritage institutions has facilitated online accessibility to numerous historical manuscripts. However, a substantial portion of these documents exists solely as images, lacking machine-readable text. Handwritten Text Recognition (HTR) has emerged as a crucial tool for converting these images into machine-readable formats, enabling researchers and scholars to analyse vast collections efficiently. Despite significant technological progress, establishing consistent ground truth across projects for HTR tasks, particularly for complex and heterogeneous historical sources like medieval manuscripts in Latin scripts (8th-15th century CE), remains nonetheless challenging.