The cognitive psychology of language – 1

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?

2. 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

3. 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

4. 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.

5. 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

6. 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

7. 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

8. 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

9. 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

10. Logogen example Let’s say the logogens fire at a threshold of 5 BAT /b/ /a/ /t/ Round Involved in sport Flying mammal Has wings Hairy Lives in the Dark BATTERY /b/ /a/ /t/ /e/ /r/ /E/ Round Electrical Guns 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.”

11. 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)

12. 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 (!)

13. 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’

14. 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