One to Rule Them All or How to Transcribe Greek Manuscripts with a HTR Model | Elpida Perdiki #TUC22
Channel: Transkribus
Date: 10/10/2022

Elpida Perdiki, Democritus University of Thrace 
One to Rule Them All or How to Transcribe Greek Manuscripts with a Single HTR Model
Historical documents remain a real-world challenge for researchers despite the existing state-of-the-art HTR technologies. A plethora of unedited or under-edited works of Greek Literature (ancient or byzantine, especially the latter) exists to this day, due to the complexity of producing critical editions. For a large manuscript tradition, such a process can be painstaking and time-consuming. To that end, HTR models trained via AI can be of great assistance. However, deep learning models require a quantum of data to be effective. This, in turn, reinforces the same problem: big data requires heavy loads of manually transcribed training sets. In absence of such transcriptions, this study experiments with training data of diverse sizes to determine the minimum amount of manual transcription needed to produce functioning results. HTR models are trained via Transkribus on several Byzantine manuscripts of a single author, John Chrysostom. Gradual reduction of training data and mixed models from multiple manuscripts proved that, if the right combination of manuscripts is selected, and by dint of Transkribus’ transfer-learning tools, the size of training sets required can be reduced by up to 80%. Certain peculiarities of Greek manuscripts, which lead to easy automated cleaning of resulting transcriptions, could further improve these results. This case study proposes a solution for researching/editing authors and works that were popular enough to survive in hundreds (if not thousands) of manuscripts and is, therefore, unfeasible to be evaluated by humans. Less could be more."