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Decipherment of Historical Manuscript Images

2019-05-24
Xusen Yin, Nada Aldarrab, Beáta Megyesi, Kevin Knight

Abstract

European libraries and archives are filled with enciphered manuscripts from the early modern period. These include military and diplomatic correspondence, records of secret societies, private letters, and so on. Although they are enciphered with classical cryptographic algorithms, their contents are unavailable to working historians. We therefore attack the problem of automatically converting cipher manuscript images into plaintext. We develop unsupervised models for character segmentation, character-image clustering, and decipherment of cluster sequences. We experiment with both pipelined and joint models, and we give empirical results for multiple ciphers.

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URL

http://arxiv.org/abs/1810.04297

PDF

http://arxiv.org/pdf/1810.04297


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