[Article] Voynich2Vec: Using FastText Word Embeddings for Voynich Decipherment
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(10-07-2020, 08:31 PM)RobGea wrote: You are not allowed to view links. Register or Login to view.Maybe the get_vectors.py script creates the model ?

Thank you. I looked at that script also and it seems to create files with a "-" in the name. It could have created models/voynich-2.vec and models/voynich-3.vec but I don't believe it can create models/voynich.bin. I am not a software wizard either: if I decide to look more into these methods, I will search for something with more documentation.



(10-07-2020, 12:26 AM)MichelleL11 wrote: You are not allowed to view links. Register or Login to view.I would have liked to have seen data similar to Table 1 from a text we knew the meaning.

The following  table is based on the models/james1.vec file in the You are not allowed to view links. Register or Login to view. linked by Torsten. The vectors are based on texts/james1.txt, this should be The political works of James I by Charles Howard McIlwain. The text is much longer than the VMS (243677 words).


I simply computed the cosine distance among all couples of vectors and picked the 100 lowest results.

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Though the main text is in English, it appears to contain some Latin. Most of the couples appear to pick the minority languages in the text: Arabic numbers and Latin.

The following table corresponds to the Spanish models/picatrix.vec, which also is much longer than the VMS (136127 words).

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It seems to me that the results are dominated by similar couples where the relationship appears to be morphological/grammatical rather than semantic ("magnesio bórax" near the bottom could be an interesting exception).
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RE: Voynich2Vec: Using FastText Word Embeddings for Voynich Decipherment - by MarcoP - 11-07-2020, 06:06 AM

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