Using Convolutional Neural Networks to Translate Cuneiform

Here’s an interesting academic paper about the potential use convolutional neural networks to translate ancient Akkadian and Sumerian from cuneiform into modern language. The Significance Statement reads:

Hundreds of thousands of clay tablets inscribed in the cuneiform script document the political, social, economic, and scientific history of ancient Mesopotamia. Yet, most of these documents remain untranslated and inaccessible due to their sheer number and limited quantity of experts able to read them. This paper presents a state of the art neural machine translation model for the automatic translation of Akkadian texts into English, from Unicode cuneiform glyphs and from transliterations of the cuneiform signs, achieving 36.52 and 37.47 Best Bilingual Evaluation Understudy 4 (BLEU4) scores, respectively. It is particularly effective in maintaining the style of the text genre in the translation. This is another major step toward the preservation and dissemination of the cultural heritage of ancient Mesopotamia.

Frater Lux Ad Mundi

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