Restoration of fragmentary Babylonian texts using recurrent neural networks

Author:

Fetaya EthanORCID,Lifshitz Yonatan,Aaron Elad,Gordin ShaiORCID

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.

Funder

Ministry of Science and Technology, Israel

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

Reference71 articles.

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2. J. Huehnergard , C. Woods , “Akkadian and eblaite” in The Cambridge Encyclopedia of the World’s Ancient Languages, R. D. Woodard , Eds. (Cambridge University Press, 2004), pp. 218–280.

3. M. P. Streck , “Akkadian in general” in The Semitic Languages: An International Handbook, S. Weninger , G. Kahn , M. P. Streck , J. C. E. Watson , Eds. (De Gruyter, 2011), pp 330–339.

4. Großes altorientalistik. Der umfang des keilschriftlichen textkorpus;Streck,2010

5. C. Gütschow , Methoden zur Restaurierung von ungebrannten und gebrannten Keilschrifttafeln (PeWe-Verlag, 2012).

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