Papers with average segmentation error

1 papers
Segmenting Numerical Substitution Ciphers (2022.emnlp-main)

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Challenge: Existing methods for deciphering historical substitution ciphers are difficult to crack . cipheries that are not segmented are still difficult to deciphere .
Approach: They propose automatic methods to segment historical substitution ciphers using BPE and unigram language models.
Outcome: The proposed methods achieve an average segmentation error of 2% on 100 monoalphabetic ciphers and 27% on 3 real historical homophonic cipheries.

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