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Unweaving the lexical rainbow: Grounding Linguistic Creativity in Perceptual Semantics


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The challenge of linguistic creativity is to use words in a way that is novel and striking and even whimsical, to convey meanings that remain stubbornly grounded in the very same world of familiar experiences as serves to anchor the most literal and unimaginative language. The challenge remains unmet by systems that merely shuttle or arrange words to achieve novel arrangements without concern as to how those arrangements are to spur the processes of meaning construction in a reader. In this paper we explore a problem of lexical invention that cannot be solved without an explicit model of the perceptual grounding of language: the invention of apt new names for colours. To solve this problem we shall call upon the notion of a linguistic readymade, a phrase that is wrenched from its original context of use to be given new meaning and new resonance in new settings. To ensure that our linguistic readymades, which owe a great deal to Marcel Duchamp’s notion of found art, are anchored in a consensus model of perception, we introduce the notion of a lexicalized colour stereotype.

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Unweaving the lexical rainbow: Grounding Linguistic Creativity in Perceptual Semantics

  1. 1. You want yer colours? I got «beaucoup de couleurs» for ya, mate.
  2. 2. We want a lawyer, pig! OK, punks!
  3. 3. My words have never carried so much meaning now that I can directly ground them via actions in the
  4. 4. Some colours make me feel While others make me see Some make me with envy!
  5. 5. @everycolorbot is a minimalist data-only Twitterbot. The bot generates a random six- digit color hex-code (for an R-G-B Red/Green/Blue mix) and a swatch of corresponding color. Though very simple, can we say that this bot’s use of RGB symbols is grounded in external visual reality?
  6. 6. Dulux uses pretentious names with positive effect, but a bot might call this one “cow urine” or “rusty battleship”. This bot would exhibit humor and visual appreciation, while grounding its use of color symbols in real stimuli. The RGB symbol-codes in @everycolorbot are not used as linguistic symbols, and are not used to convey semantics. What if we build a bot that assigns meaningful color names to these arbitrary RGB symbols?
  7. 7. First, let’s ground the meaning of color words in actual RGB codes that a computer can render on screen. When a bot combines color words, it can also combine their RGB color codes. A compositional semantics for linguistic symbols is paired to a compositional semantics for RGB codes, so that we can also ground the meaning of complex phrases.
  8. 8. We can use Web n-grams to suggest attested combinations of our color stereotypes, such as “paper tiger” and “rose garden”. Readymade combinations of words make much more sense than purely random ones.
  9. 9. The lower the n-gram frequency, the less conventional the readymade ... … so the more striking and unusual the color name that can be derived.
  10. 10. Questions / Judgments @HueHueBot (Machine names) (Human names) Q1: Most Descriptive name 70.4% 29.6% Q2: Most Preferred name 70.2% 29.8% Q3: Most Creative name 69.1% 30.9%