Restoration of fragmentary Babylonian texts using recurrent neural networks.

Abstract:

:The main sources of information regarding ancient Mesopotamian history and culture are clay cuneiform tablets. Many of these tablets are damaged, leading to missing information. Currently, the missing text is manually reconstructed by experts. We investigate the possibility of assisting scholars, by modeling the language using recurrent neural networks and automatically completing the breaks in ancient Akkadian texts from Achaemenid period Babylonia.

authors

Fetaya E,Lifshitz Y,Aaron E,Gordin S

doi

10.1073/pnas.2003794117

subject

Has Abstract

pub_date

2020-09-15 00:00:00

pages

22743-22751

issue

37

eissn

0027-8424

issn

1091-6490

pii

2003794117

journal_volume

117

pub_type

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