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The cognitive psychology of language – 1. The previous lecture covered mostly linguistics The study of languages as independent structures Can apply to human languages as well as machine languages Now focus on how cognitive psychology can explain human language

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the cognitive psychology of language 1
The cognitive psychology of language – 1
  • The previous lecture covered mostly linguistics
    • The study of languages as independent structures
    • Can apply to human languages as well as machine languages
  • Now focus on how cognitive psychology can explain human language
    • Where is syntax stored? How are resources used to apply the rules?
    • How do we recognise words from sounds?
recognizing speech
Recognizing speech
  • Recognition of words in speech is extremely good
    • Subjects recognized words after 270 msec of speech, even though the words lasted 370 msec!
  • Variations do not greatly affect recognition
    • Speed, volume and pitch have almost no effect
    • Recognition rate with completely unfamiliar voice same as with familiar voice
what affects recognition
What affects recognition?
  • More common words are recognized faster
    • ‘practice effect’
    • Can pick a single phoneme from common words much faster than from uncommon ones
  • Sentence context improves recognition
    • The same word in a sentence is recognized faster that if it is presented alone
    • Expectation (top-down) helps recognition process
context recognition
Context & Recognition
  • Semantic priming contributes to recognition

Teddy bears are good for little children

Teddy bears are good for hungry children

  • ‘children’ will be recognized faster in the first sentence
    • The beginning of the sentence limits the possible options
  • Semantic priming can be quite a strong effect (‘sentence superiority’)

As the sun set and evening fell, the pale mcqn rose over the horizon.

context is cross modal
Context is cross-modal
  • It does not matter if the priming is done via reading or speech
    • You can mix ‘em up and it still works.
    • Shows it works at a language level rather than a vision or auditory level
  • Play the priming sentence via headphones, show three words in writing (Swinney, 1979)
    • One unrelated word
    • One word related semantically to the entire sentence
    • One word semantically related to the last word of the priming sentence
swinney example
Swinney Example
  • Audio: “The aircraft was fueled, and the crew had finished filing a flight plan.”
    • Words shown: PILOT, TOMATO, BUILDING
    • Ranking of speed recognition: PILOT, BUILDING, TOMATO
  • PILOT was recognized fastest due to being primed by the sentence as a whole
  • BUILDING was only primed by the last word (plan), so was recognized more slowly
  • TOMATO was recognized slowest, because it was not primed at all
lexical access
Lexical Access
  • Where are the words stored?
    • The lexicon is the word storage
  • Lexicon holds all aspects of a word
    • Spelling, meaning, pronunciation, role in syntax
  • The lexicon is huge
    • Average American female office worker, age 50

known well: 30,000

known vaguely: 8,000

used often: 16,000

used occasionally: 15,000

  • Very rare to find someone pausing to think of a word
    • Lexical access is extremely fast
lexical access models
Lexical access models
  • Two classes of model
    • Direct access
    • Serial search
  • Direct access models
    • Posit that the lexicon contains some sorting information
    • ‘bookmarks’ to word features
    • Allows considering multiple words at once for a search
  • Serial search models
    • No additional information needed
    • Order of storage may be important
    • Can only consider one word at a time
the logogen model morton 1969
The Logogen model (Morton, 1969)
  • A threshold based direct access model
  • Each item in the lexicon is a logogen
    • A ‘feature counter’ which accumulates evidence
    • Features can be sensory, contextual, anything
  • Logogens build up evidence until a threshold is reached
    • Then it ‘fires’ and the word is recognized
logogen example
Logogen example

Let’s say the logogens fire at a threshold of 5


/b/ /a/ /t/


Involved in sport

Flying mammal

Has wings


Lives in the Dark


/b/ /a/ /t/ /e/ /r/ /E/




Can shock

Has wires attached

Eventually goes dead

“The light wouldn’t go on, so I checked the wires, but then it turns out that the battery was dead.”

discussion logogen model
Discussion: Logogen model
  • Morton later adapted threshold of logogens
    • Included the idea of ‘activation decay’ (lowered threshold)
    • Logogens encoding common words have lower thresholds
  • Precursor to connectionist model
    • Lacking multi-layer architecture (esp. hidden layers)
    • No competition or inhibition
    • No clear idea of learning (in logogen content)
the cohort model marlsen wilson 1973
The cohort model (Marlsen-Wilson, 1973)
  • Sequential, on-line model of word recognition
  • The first two phonemes used as a filter to select ‘initial cohort’ of likely words
    • As more phonemes are heard, candidates that don’t fit are discarded, and the cohort shrinks until you only get one word left
  • Very similar to the T9 predicitive text input on your cell phone (!)
cohort model example
Cohort model example
  • You hear /e//r/
  • Initial list
    • “aircraft”, “error”, “erode”, “air”, “erroneous”
  • Next you hear /o/
    • That rules out “aircraft”, “air”, “erode”
  • Next you hear /n/
    • That rules out “error”, so it must have been ‘erroneous’
discussion of the cohort model
Discussion of the cohort model
  • Context does not affect the cohort
    • The cohorts are the same regardless of priming
    • Priming helps recognition because it speeds up linking the word to higher representations
  • The decision process is not passive
    • Logogen model – activation increases with no effort
    • In the cohort model, words must be actively rejected from the cohort