Restoring ancient text using deep learning: a case study on Greek epigraphy

Understand

Ancient history relies on disciplines such as epigraphy, the study of ancient inscribed texts, for evidence of the recorded past.

• However, these texts, "inscriptions", are often damaged over the centuries, and illegible parts of the text must be restored by specialists, known as epigraphists.
• This work presents Pythia, the first ancient text restoration model that recovers missing characters from a damaged text input using deep neural networks.
• Its architecture is carefully designed to handle long-term context information, and deal efficiently with missing or corrupted character and word representations.