Torsten > 16-10-2019, 01:22 PM
Quote:The most interesting results are, however, those obtained with the observation probability matrix, which clearly separate two kinds of characters to be associated with vowel and consonant phonemes ... On the other hand, this correspondence is not as strong as in the case of the English text of Section 3.1 because there are symbols with noticeable probability that appear in both figures (in particular, the EVA symbols 'e', 'i', 's' and 'y').
davidjackson > 16-10-2019, 07:49 PM
Quote:We started with the same initial conditions as those given in Equations (11) and (12) for the
transition matrix and the distribution of the state t=0. The probability matrix for the observation
states (the Voynich characters) was randomized in the usual way explained in Section 3.1.
Quote:At this point, it is also be necessary to explain why we chose this particular alphabet [EVA] instead
of the other alternatives. The main reasons are its popularity and the fact that many transcriptions
are available for it. Otherwise, some specialists would argue that some symbol combinations in this
alphabet, such as “ch” and “sh”(corresponding to the so-called “pedestals”) should be considered as
one single character each. On the other hand, the combinations “in” and “iin” are also candidates
for representing letters, although, in some other cases, “i” could be a single character. This is another
problem that computational analyses could help to solve [...]
This way, a transcription of the whole Voynich manuscript has been performed in such a way
that it can be used in computational analysis. [..] In particular, we used Takahashi’s transcription developed in 1999.
Of course, some pre-processing was required before applying the HMM algorithm because this ﬁle
includes some information about each line, including the folium number (recto or verso) and the
number of the line within each page of the manuscript. After removing this information, we were left
with a set of EVA characters separated by dots. These dots correspond to the spaces between words in
the original manuscript.
ReneZ > 16-10-2019, 08:13 PM
(16-10-2019, 07:49 PM)davidjackson Wrote: You are not allowed to view links. Register or Login to view.The author explains:
Quote:We started with the same initial conditions as those given in Equations (11) and (12) for the
transition matrix and the distribution of the state t=0. The probability matrix for the observation
states (the Voynich characters) was randomized in the usual way explained in Section 3.1.
In other words, he used initialised the HMM using results found from his previous analysis of an English language translation of Don Quijote (Equations (11) and (12) being biased for the English language text).
davidjackson > 16-10-2019, 08:28 PM
(16-10-2019, 08:13 PM)ReneZ Wrote: You are not allowed to view links. Register or Login to view.No, that's not correct. These are completely arbitrary initial conditions that are slightly off from 'all probabilities equal', to avoid that the process gets stuck from the very beginning.Really? Obviously you have far more experience than I do in these things, but I read it as he initialised the algorithm with random values as explained in part 2.3) (equations 6-10) then reestimated and used the same values to carry out both runs (init values for equations 11-12).
Quote: First, we consider the case of a text in English and we implement the model optimization
algorithm to classify the letters of the alphabet (after removing all the punctuation signs) into two
classes corresponding to the inner states of the HMM. It is shown that these classes are clearly associated
with the vowels and the consonants in English and this provides the basic phonemic structure of the
language. Testing the algorithm with a known language gives us the necessary conﬁdence to apply it
to the Voynich manuscript.
ReneZ > 17-10-2019, 05:40 AM
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davidjackson > 17-10-2019, 08:18 PM
Torsten > 21-10-2019, 07:52 PM
ReneZ > 22-10-2019, 06:10 AM
MarcoP > 22-10-2019, 05:56 PM