Computational methods for undeciphered scripts

Abstract

The study of ancient, undeciphered scripts through computational means presents unique challenges that depend both on the nature of the problem and on the peculiarities of each writing system. This volume presents two computational approaches that were successfully applied to two writing systems from the Aegean and Cyprus; the success of these endeavors paves the way for new discoveries and methods. The first part features a discussion of the Linear A and Cypro-Minoan writing systems, as well as a background of the computational approaches used. The description of the paleographic and technical aspects is aimed at scholars of both disciplines and provides an extensive background, which is crucial to understanding the goals and methods of this study. The second part is a discussion of the experimental results, which includes a proposed decipherment of the Linear A fractions. Further, the experiments on Cypro-Minoan demonstrate that, contrary to previous hypotheses, it is a single writing system, rather than comprising three separate systems. The two experiments used completely different computational methods, since the method used to decipher Linear A is based on constraint programming, while the Cypro-Minoan experiments are based on a deep learning model. Michele Corazza is a research fellow at the University of Bologna in the field of natural language processing. After obtaining his master’s degree in computer science, he joined the WIMMICS team in INRIA Sophia Antipolis, France, working as a research engineer on the CREEP project, focused on the detection and prevention of cyberbullying online. During this collaboration he developed machine learning models that detect hate speech and cyberbullying on social networks in a multilingual setting. In 2019 he started a PhD at the University of Bologna, joining the INSCRIBE ERC project, which investigates the origin of writing. His PhD studies focused on the development of computational methods based on writing systems in the Aegean and Cyprus, in particular Linear A and Cypro-Minoan. After defending his thesis in 2023, he joined the HyperModeLex ERC project, which is focused on developing AI models to aid in the European legislative process.