Notes from “Virtual Muse”

Some notes from “Virtual Muse: Experiments in Computer Poetry” by Charles Hartman (1996).  Page numbers are indicated in parentheses.

  • “A neuron has no mind” (3)
  • The idea of nonsense as different from meaningless, quoted from Lewis Carroll’s Jabberwocky:
    “‘Twas brillig, and the slithy roves/Did gyre and gimble in the wabe”
  • “The syntactical system of English, which Carroll leaves intact while disrupting the vocabulary, carries a far greater proportion of the meaning of a sentence than we’re usually aware of.” (19)
  • “Understanding isn’t additive.  Meaning doesn’t accumulate word by word as we trudge through a sentence.  It precipitates, as rain precipitates out of air under the right conditions… Reading takes place within a context, and the context is present at the reading because the reader brings it along… Sense is never absolutely continuous; there are irreducible gaps.  Poetry tends to make us more aware of the gaps than does conversation or political speeches.” (21)
  • “Language is a ‘structure of differences’ [referring to Ferdinand de Saussure] in the sense that words don’t get their meaning directly from referring to things in the world.  They get their meaning from their relations to other words… Many words have meaning only because of their relations within that system: which, the, only, and so on.” (26)
  • For a long while I have been interested in outmoded, cumbersomely-created books that, due to time and technology, are relics: the concordance is such a text. “The classic literary computer project is the concordance: a list of all the words that appear in a certain work (or all the works by a certain author or, in the grandest concordance so far, the Thesaurus Linguae Graecae, the whole of classical Greek literature).  The list is arranged in alphabetical order for easy reference, preferably with an indication of the context for each appearance of the word.” (38)
  • Generative linguistics (41)
  • The “Travesty” program: “A text, such as a passage from a novel, is among other things a set of characters.  It consists of so many e’s, so many f’s, and so on.  It’s also a set of character pairs (so many ex’s, so many ch’s, etc) and of triplets (the’s, wkw’s, etc), and so on… From [a frequency table], another text can be constructed that shares statistical properties, but only those properties, with the first one.  That’s what Travesty does.  It produces an output text that duplicates the frequencies of n-character groupds in the input text.  To put the same thing the other way, it thoroughly scrambles its input text but only down to level n.

    n=1: “Dengethe pr: o ls h thee.  wicach Ye thur.  obbug lesila thicateronoisthate Thrit O athe are. t is: winsict kerprurise, y m? the o mor sty hetseatheancathensous.”

    n=9: “Dead flies cause the ointment of the apothecary to send forth a stinking savour: so doth a little folly him that is in reputation for wisdom and honour.  A wise man’s heart is at his right hand; but a fool’s hear at his left.”

  • “Now I had my program; but what to do with it? The first thing I tried was the easiest.  I let it run for a while and then combed through the output looking for interesting chunks I could string together.  But this approach held onto a residue of my earlier false assumption.  I was still treating the computer as a retarded or psychotic human brain from which I could hope for flashes (however far apart) of ordinary or extraordinary lucidity.” (82)
  • Apparently, Roget’s “Thesaurus” has a “synopsis of categories” which contains “all the possible things to talk about in an orderly outline.” (94)
  • “How do words mean when we put them into new contexts? Under what conditions does the meaning web tear apart?  What meanings can words make (or can we make of them) when we disturb their normal relation to each other?” (104)
  • “It’s worth making a three-way distinction among the random, the arbitrary, and the contingent… If we get rid of contingency entirely, replacing it with purely random or arbitrary linguistic acts, we get genuine gibberish.  The point, rather, is to introduce calculated bits of mechanized anarchy into the language, put the results back into the contingent world where language lives, and see how the dust settles.” (109)

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