Hybrid Workshop - Automated Text Recognition of Historical Sources: From convolutional neural networks to vision language models
3rd floor, seminary rooms 2 and 3
Austrian Academy of Sciences
Automated or Handwritten Text Recognition has been making continuous progress, with new tools, models, and technologies emerging every year. This rapidly evolving field is becoming a "must-have" for many digital endeavors, particularly in the study of historical sources. There are, however, still multiple challenges, e.g., complicated page layouts, lack of models for some languages and scripts, Latin abbreviations, and inconsistencies in the training data.

Used images. Top: ÖNB, Cod. 15298 HAN MAG, fol. 3r; SBzB Ms Or fol 248;ÖNB, 1175, 4r; ÖNB, Cod. 387 HAN MAG, fol. 117r; BNB, Pelliot tibétain 999
Bottom: The Walters Art Museum, W.537.2V; ÖNB, Cod. 3891, fol. 1r; CFMM 00567; ÖNB, G 16715 PAP MAG
This hybrid workshop at the Austrian Academy of Sciences will showcase a variety of case studies and projects from researchers based in Vienna, Graz, and Innsbruck, along with a guest presentation by David Smith from Northeastern University.
The event will conclude with a round table discussion on the present and future of Automated Text Recognition, featuring (in alphabetical order):
- Anna Dolganov
- Günter Mühlberger
- Jan Odstrčilík
- David Smith
- Georg Vogeler
We invite you to join us to explore the latest developments in ATR.
The event is organised by:
- Digital Lab, Institute for Medieval Research (IMAFO), Austrian Academy of Sciences
- Austrian Archaeological Institute (OeAI), Austrian Academy of Sciences
- Faculty of Historical and Cultural Studies at the University of Vienna
Supported by:
- Machine Learning Topical Platform (MLA2S), Austrian Academy of Sciences
Organisational team:
- Jan Odstrčilík, Helmut Reimitz (IMAFO)
- Anna Dolganov (ÖAI)
- Thomas Wallnig (University of Vienna)



