MarkovMutagen
“The true literature machine will be one that itself feels the need to produce disorder, as a reaction against its preceding production of order: a machine that will produce avant-garde work to free its circuits when they are choked by too long a procession of classicism.”
Inputs
Search for .epub files on Library Genesis
Add a Project Gutenburg or Archive.org url.
A random Project Gutenburg document will be selected.
and words
Outputs
About Markov Chains
A Markov chain is a stochastic model describing a sequence of possible events in which the probability of
each event
depends only on the state attained in the previous event. In the case of text generation, these
probabilities are
determined by word order of an input, which can be broken down into n-grams (units) of 1, 2, or 3 words.
For
the order-1
n-gram model, Markov text generation begins by selecting random word which begins a sentence and then
selects a random
word which followed that word, weighted by frequency of appearance: for instance, if in the input "The" is
followed by
"rhombus" thrice and "skeleton" once, there is a 75% chance the algorithm will select rhombus next and a 25%
chance
skeleton will be selected. If skeleton is selected, the word which follows skeleton in the original text
will appear
next, since skeleton appeared only once, but if rhombus is selected, then a random word which follows
rhombus in the
original passage will appear. The order 2 n-gram variant would proceed similarly, except it would start by
randomly
selecting "The rhombus" or "The skeleton" and then, if "The rhombus" was selected, randomly select a word
which followed
"The rhombus."
Use in Literature
By running multiple texts together through a Markov chain at the same time, it becomes possible to collage
bits of text
in novel, often nonsensical ways that often rebel from syntax and invert idiomatic constructions. (Software,
after all,
has no subconscious to veto awkward constructions before they arise to conscious thought.)
There are several
precedents
to this technique. The cut-up technique, pioneered by the Dadaists and further developed by William S.
Burroughs and
Brion Gysin, rearranged cut-up blocks of text from multiple pages to invent a new body of text. In the
1980s,
programmers realized the parodic potential of Markov chain algorithms when applied to writing and released
Dissociated
Press, a plug-in for the eMacs text editor. Following in their footsteps, Jamie Zawinski released the
C program
dadadodo which generates
text from an input file.
Markov Mutagen
With Markov Mutagen, you can easily combine and run inputs through a Markov text generator or a simulation
of the cut-up
technique. You are encouraged to combine, edit, and collage the outputs or even recycle the output as an
input.
Cybernetic writing is an open-ended game whose procedures are still being developed and combined in new
ways.
So try
sampling text from a novel, news article, encyclopedia, conspiracy theory, theological treatise, or whatever
else
strikes your fancy. Try replacing a word (noun, verb, adjective) in one input with a word from another to
manipulate the
probabilities in the Markov model. The outputs of neural networks like TalkToTransformer also serve well as
inputs. And
enjoy the fruits of your discordant prosody.