Re: VMs: RE: RE: Best-fit 2-state PFSMs

[steve ekwall <ekwall2@xxxxxxxx>]

Speaking of 2-state(s): what is the currently accepted(?) 
letters/elements in the vms now for its alphabet? 
Wasn't it something like 14 or so? 
IF that number were DOUBLED (as in MIRRORed) to 28 or so,
then how many _Different Languages_ would "28" cover..
inluding $ signs and @ & # signs etc (if needed/ or not) 

Folding would make it Twice as big as it appears etc..

-=se=-
steve (still folding/mirroring) ekwall
 

 Date: Fri, 11 Mar 2005 00:10:06 -0600
 From: Dennis <tsalagi@xxxxxxxx>
 Subject: Re: VMs: RE: RE: Best-fit 2-state PFSMs
 
 Nick Pelling wrote:
 
 	Not necessarily regarding (P)FSM's,
 
 > Really, I think that Voynichese is only superficially language-like, and 
 > that it has an innate artificiality at its core. The idea behind 
 > examining its structure by incrementing the number of target states is 
 > to try to find a kind of transition point between the superficial 
 > language-like structure and whatever lies beneath.
 > 
 >>   Real languages apparently can't be
 >> realistically modeled without very, very large FSMs, so if a drop like
 >> this occurred, it may not happen until the FSM has hundreds of states.
 >> The largest I've ever tried to generate was 120 states.
 
 	What effect does the size of the text corpus have?  The HMM 
 needed a text corpus of ~6 Mbyte for a clear result.  Would 
 it tell us something to create an enormous synthetic 
 Voynichese corpus by Gabriel or Jeff's method or Stolfi's 
 Voynichese grammar and then analyze it?
 
 > FWIW, I suspect the transition point will fall between 10 and 20 states 
 > (for a pre-paired transcription set, such as one where qo / ol / or / al 
 > / ar / iiii / iii / ii / eeee / eee / ee / dy / cfh / ckh / cph / cth / 
 > ch / sh / eo / od all map to single tokens). For EVA, the PFSM finder 
 > would also have to unpick all the tricky pairing rules correctly (lots 
 > of local minima to avoid), so I guess 60+ states would be closer there.
 
 	What about defining a transcription alphabet that treats 
 these digraphs/verbose cipher elements as single glyphemes 
 and then analyzing the VMs in that transcription?    That 
 seems like a useful exercise.
 
 Dennis
 
 
 > 
 > Cheers, .....Nick Pelling.....
 > 
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