The rapid disappearance of global linguistic diversity has prompted an urgent shift toward Digital Archaeology—a field utilizing computational power to preserve and resurrect extinct languages. This paper details the application of Transformer-based Neural Decipherment and Acoustic Phonetic Reconstruction to recover lost dialects from the 1st millennium BCE. By processing fragmented epigraphic data and cross-referencing cognate patterns in surviving daughter languages, we demonstrate the successful reconstruction of a "proto-dialect" previously undocumented in the Southern Arabian Peninsula. Our findings suggest that AI can fill "lexical gaps" in damaged inscriptions with an accuracy rate of 89%. This study highlights the role of digital twins in archiving the intangible heritage of humanity, ensuring that lost languages remain accessible for future historical and cognitive research.
Marcus Thorne, Laila Al-Farsi, Chen Wei (2026) studied this question.