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

By Yannis Assael, Thea Sommerschield, Jonathan Prag. 2019

78 citations recorded by the source corpus.

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. To train it, we wrote a non-trivial pipeline to convert PHI, the largest digital corpus of ancient Greek inscriptions, to machine actionable text, which we call PHI-ML. On PHI-ML, Pythia’s predictions achieve a 30.1% character error rate, compared to the 57.3% of human epigraphists. Moreover, in 73.5% of cases the ground-truth sequence was among the Top-20 hypotheses of Pythia, which effectively demonstrates the impact of this assistive method on the field of digital epigraphy, and sets the state-of-the-art in ancient text restoration.

Subfields: Computer Vision and Pattern Recognition, Literature and Literary Theory, Natural Language Processing

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Citations in the corpus

InCoder: A Generative Model for Code Infilling and Synthesis (2022, background): “, editing sentences [57], restoring ancient text [9], and fixing bugs in source code.”
Enabling Language Models to Fill in the Blanks (2020, background): “1 Systems capable of inﬁlling have the potential to enable rich applications such as assisting humans in editing or revising text (Shih et al., 2019), connecting fragmented ideas (AI21, 2019), and restoring ancient documents (Assael et al., 2019).”
Blank Language Models (2020, methodology): “Dataset The PHI-ML dataset (Assael et al., 2019) is made of fragments of ancient Greek inscriptions containing more than 3 million words and 18 millions characters.”