Vord paradigm tool

[Torsten]

For me, this is not a problem. If the MS text was the result of a truly arbitrary process, then we would expect to be able to predict such frequencies, but in case it is meaningful language, then not.

Compare English:

bat - bet - bit - bot - but
cat - cet - cit - cot - cut

Tehre is no pattern in the frequencies
(Dislcaimer: just the first example I could think of).

Words in the Voynich text doesn't behave like in the "bat - bet - bit - bot - but" example. There is not only a small 2 dimensional grid but a whole network:
qokeedy (305) qokeedy (305) qokeedy (305)    qoteedy (74) qoteedy (74) qoteedy ( 74)
qokedy  (272)  qokeey (308)  okeedy (105)    qotedy  (91)  qoteey (42)  oteedy (100)
qokdy   (  4)   qokey (107)   keedy ( 53)    qotey   (24)   qotey (24)   teedy ( 13)

qoky    (147)    qoky (147)    kedy ( 44)    qoty    (87)    qoty (87)    tedy ( 42)

qok     (  9)     qoy (  9)     key ( 14)    qot     ( 7)     qoy ( 9)     tey ( 11)

qo      ( 29)      qy (  3)      ky ( 25)    qo      (29)      qy ( 3)      ty ( 16)

To achieve something similar longer words and multiple changes would be required. Something like:
   acaut  aceut  aciut  acout   acuut
    acat   acet   acit   acot    acut
     cat    cet    cit    cot     cut
     bat    bet    bit    bot     but 
    abat   abet   abit   abot    abut
   abaut  abeut  abiut  about   abuut



There are patterns in the frequencies, e.g. <ee> is more common than <e> and <eee> and <ok> tends to be more common than <ot>. The general rule is that "high frequency tokens also tend to have high numbers of similar words" [see Timm & Schinner 2019, p. 6].

qokeeedy (  5)  qoteeedy (  3)
 qokeedy (305)   qoteedy ( 74)
  qokedy (272)    qotedy ( 91)

 qokeeey ( 26)   qoteeey (  4)
  qokeey (308)    qoteey ( 42)
   qokey (107)     qotey ( 24)

 okeeedy (  9)   oteeedy (  3)
  okeedy (105)    oteedy (100)
   okedy (118)     otedy (155)