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A Hidden Markov Model for the Linguistic Analysis of the Voynich’s Manuscript
Version 1
: Received: 23 November 2018 / Approved: 26 November 2018 / Online: 26 November 2018 (14:02:40 CET)
A peer-reviewed article of this Preprint also exists.
Acedo, L. A Hidden Markov Model for the Linguistic Analysis of the Voynich Manuscript. Math. Comput. Appl. 2019, 24, 14. Acedo, L. A Hidden Markov Model for the Linguistic Analysis of the Voynich Manuscript. Math. Comput. Appl. 2019, 24, 14.
Abstract
Hidden markov models are a very useful tool in the modelling of time series and any sequence of data. In particular, they have been successfully applied to the field of mathematical linguistics. In this paper, we apply a hidden markov model to analyze the underlying structure of an ancient and complex manuscript, known as Voynich's manuscript, that remains still undeciphered. By assuming a certain number of internal states representations for the symbols of the manuscript we train the network by means of the $\alpha$ and $\beta$-pass algorithms to optimize the model. By this procedure, we are able to obtain the so-called transition and observation matrices in order to compare with known languages concerning the frequency of consonant and vowel sounds. From this analysis, we conclude that transitions occur between the two states with similar frequencies to other languages. Moreover, the identification of the vowel and consonant sounds matches some previous tentative bottom-up approaches to decode the manuscript.
Keywords
Hidden Markov Models; Mathematical Linguistics; Voynich Manuscript
Subject
Computer Science and Mathematics, Computational Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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