The advert is live for the Collaborative Doctoral Partnership (University of Nottingham & BM, together with CSAD and the Vindolanda Trust) project on the Vindolanda tablets (ink and stylus) - using the latest imaging and AI to attempt a range of tasks including reassembling fragments, handwritten text recognition, disentanglement of palimpsest texts etc. Deadline for applications is Monday 2 June.
The Vindolanda tablets are an unrivalled documentary source for the Roman army and its activities in Roman Britain. The research will examine if Generative Artificial Intelligence (AI) can support the recovery of the handwritten Latin texts and in turn how this might be applied to aid the decipherment of other similar objects across the British Museum collections.
Although much work has been carried out on the tablets, numerous texts are not deciphered, and the work to recover them is painstaking. A quarter of a century ago, research was undertaken to see if computers might help (Terras 2006 Image to Interpretation: An Intelligent System to Aid Historians in Reading the Vindolanda Texts), but the disproportionate effort required did not encourage development. Now massively increased computing power and the success of Generative AI in various ancient world applications (Sommerschield et al. 2023 ‘Machine Learning for ancient languages: A survey’, Computational Linguistics, 49.3) mean that it is time to test the latest digital tools (e.g. GPT-4o) to undertake four main tasks:
- identify and recognise handwritten characters;
- digitally reassemble fragments;
- restore missing text when objects are fragmentary or text has been lost;
- decipher palimpsest (overlying) texts.
These tasks would be undertaken using Generative AI pipelines that have already been created for Greek papyri (e.g. Swindall), oracle bones (e.g. Zhang), and cuneiform tablets (e.g. Dahl) and have the potential to bring new texts to light from the extraordinary Vindolanda collection, and to create improved models which could be applied to other BM collections.
More information about the project and how to apply can be found here:
https://jobs.nottingham.ac.uk/Vacancy.aspx?ref=ARTS124.
