arXiv Open Access 2020

Solving Historical Dictionary Codes with a Neural Language Model

Christopher Chu Raphael Valenti Kevin Knight

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Abstrak

We solve difficult word-based substitution codes by constructing a decoding lattice and searching that lattice with a neural language model. We apply our method to a set of enciphered letters exchanged between US Army General James Wilkinson and agents of the Spanish Crown in the late 1700s and early 1800s, obtained from the US Library of Congress. We are able to decipher 75.1% of the cipher-word tokens correctly.

Topik & Kata Kunci

cs.CL

Penulis (3)

Christopher Chu

Raphael Valenti

Kevin Knight

Format Sitasi

APA MLA BibTeX

Chu, C., Valenti, R., Knight, K. (2020). Solving Historical Dictionary Codes with a Neural Language Model. https://arxiv.org/abs/2010.04746

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓