PSY 369: Psycholinguistics

1. PSY 369: Psycholinguistics Language Comprehension: Sentence comprehension

2. Language perception Word recognition Syntactic analysis Semantic & pragmatic analysis Input c dog a cat cap S t wolf The cat chased the rat. VP NP tree V NP /k/ yarn cat the chased the rat /ae/ cat claw /t/ fur hat Overview of comprehension

3. Eye-movements in reading • One of the most common measures used in sentence comprehension research is measuring Eye-movements Clothes make the man. Naked people have little or no influence on society. Clothes make the man. Naked people have little or no influence on society.

4. Eye-movements in reading • One of the most common measures used in sentence comprehension research is measuring Eye-movements Clothes make the man. Naked people have little or no influence on society. Clothes make the man. Naked people have little or no influence on society.

5. The Human Eye • At its center is the fovea, a pit that is most sensitive to light and is responsible for our sharp central vision. • The central retina is cone-dominated and the peripheral retina is rod-dominated.

6. Retinal Sampling

7. Retinal Sampling

8. Eye-movements in reading • Limitations of the visual field • 130 degrees vertically, 180 degrees horizontally (including peripheral vision • Perceptual span for reading: 7-12 spaces Clothes make the man. Naked people have little or no influence on society.

9. Measuring Eye Movements Purkinje Eye Tracker • Laser is aimed at the eye. • Laser light is reflected by cornea and lens • Pattern of reflected light is received by an array of light-sensitive elements. • Very precise • Also measures pupil accomodation • No head movements

10. Measuring Eye Movements Video-Based Systems • Infrared camera directed at eye • Image processing hardware determines pupil position and size (and possibly corneal reflection) • Good spatial precision (0.5 degrees) for head-mounted systems • Good temporal resolution (up to 500 Hz) possible

11. Eye Movements • Within the visual field, eye movements serve two major functions • Saccades to Fixations – Position target objects of interest on the fovea • Tracking – Keep fixated objects on the fovea despite movements of the object or head

12. Fixations • The eye is (almost) still – perceptions are gathered during fixations • The most important of eye “movements” • 90% of the time the eye is fixated • duration: 150ms - 600ms

13. Saccades • Saccades are used to move the fovea to the next object/region of interest. • Connect fixations • Duration 10ms - 120ms • Very fast (up to 700 degrees/second) • No visual perception during saccades • Vision is suppressed • Evidence that some cognitive processing may also be suppressed during eye-movements (Irwin, 1998) Video examples: 1 | 2 | 3 | 4

14. Saccades Move to here

15. Saccade w/o suppression

16. Saccades Move to here

17. Saccades

18. Saccades • Saccades are used to move the fovea to the next object/region of interest. • Connect fixations • Duration 10ms - 120ms • Very fast (up to 700 degrees/second) • No visual perception during saccades • Vision is suppressed • Ballistic movements (pre-programmed) • About 150,000 saccades per day

19. Smooth Pursuit • Smooth movement of the eyes for visually tracking a moving object • Cannot be performed in static scenes (fixation/saccade behavior instead)

20. Saccades Jerky No correction Up to 700 degrees/sec Background is not blurred (saccadic suppression) Smooth pursuit Smooth and continuous Constantly corrected by visual feedback Up to 100 degrees/sec Background is blurred Smooth Pursuit versus Saccades

21. Eye-movements in reading • Eye-movements in reading are saccadic rather than smooth Clothes make the man. Naked people have little or no influence on society. Video examples: 1 | 2 | 3 | 4

22. dog The man hit the with the leash. S NP det N The man

23. dog The man hit the with the leash. S NP VP V det N The man hit

24. dog The man hit the with the leash. S NP VP V NP NP det N det N The man hit the dog

25. PP with the leash dog The man hit the with the leash. S NP VP V NP NP Modifier det N det N The man hit the dog

26. PP with the leash dog The man hit the with the leash. S NP VP V NP Instrument NP det N det N The man hit the dog

27. dog The man hit the with the leash. • How do we know which structure to build?

28. Parsing • The syntactic analyser or “parser” • Main task: To construct a syntactic structure from the words of the sentence as they arrive • Main research question: how does the parser “make decisions” about what structure to build?

29. Different approaches • Immediacy Principle: access the meaning/syntax of the word and fit it into the syntactic structure • Serial Analysis (Modular): Build just one based on syntactic information and continue to try to add to it as long as this is still possible • Interactive Analysis: Use multiple levels (both syntax and semantics) of information to build the “best” structure

30. Interactive models Sentence Comprehension • Modular

31. Different approaches • Immediacy Principle: access the meaning/syntax of the word and fit it into the syntactic structure • Serial Analysis (Modular): Build just one based on syntactic information and continue to try to add to it as long as this is still possible • Interactive Analysis: Use multiple levels (both syntax and semantics) of information to build the “best” structure • Parallel Analysis: Build both alternative structures at the same time • Minimal Commitment: Stop building - and wait until later material clarifies which analysis is the correct one.

32. Sentence Comprehension • A vast amount of research focuses on: Garden path sentences • A garden path sentence invites the listener to consider one possible parse, and then at the end forces him to abandon this parse in favor of another.

33. Real Headlines • Juvenile Court to Try Shooting Defendant • Red tape holds up new bridge • Miners Refuse to Work after Death • Retired priest may marry Springsteen • Local High School Dropouts Cut in Half • Panda Mating Fails; Veterinarian Takes Over • Kids Make Nutritious Snacks • Squad Helps Dog Bite Victim • Hospitals are Sued by 7 Foot Doctors

34. S NP VP The horse Sentence Comprehension • Garden path sentences • The horse raced past the barn fell.

35. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. S NP VP V The horse raced

36. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. S NP VP V PP P NP The horse raced past

37. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. S NP VP V PP P NP The horse raced past the barn

38. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. S NP VP V PP P NP The horse raced past the barn fell

39. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. • raced is initially treated as a past tense verb S NP VP V PP P NP The horse raced past the barn

40. Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. • raced is initially treated as a past tense verb • This analysis fails when the verb fell is encountered S NP VP V PP P NP The horse raced past the barn fell

41. S VP NP V NP RR PP V P NP The horse raced past the barn fell Sentence Comprehension • Garden path sentences • The horse raced past the barn fell. • raced is initially treated as a past tense verb • This analysis fails when the verb fell is encountered • raced can be re-analyzed as a past participle. S NP VP V PP P NP The horse raced past the barn fell

42. A serial model • Formulated by Lyn Frazier (1978, 1987) • Build trees using syntactic cues: • phrase structure rules • plus two parsing principles • Minimal Attachment • Late Closure • Go back and revise the syntax if later semantic information suggests things were wrong

43. A serial model • Minimal Attachment • Prefer the interpretation that is accompanied by the simplest structure. • simplest = fewest branchings (tree metaphor!) • Count the number of nodes = branching points The girl hit the man with the umbrella.

44. Minimal attachment S 8 Nodes NP VP the girl V NP Preferred S hit NP PP NP VP the man P NP the girl V NP PP with the umbrella hit the man P NP with the umbrella 9 nodes The girl hit the man with the umbrella.

45. A serial model • Late Closure • Incorporate incoming material into the phrase or clause currently being processed. OR • Associate incoming material with the most recent material possible. She said he tickled her yesterday

46. Parsing Preferences .. late closure S Preferred S np vp np vp she v S' adv she v S' said np vp yesterday said np vp he v np he v np adv tickled her tickled her yesterday (Both have 10 nodes, so use LC not MA) She said he tickled her yesterday

47. Modular prediction Interactive prediction Minimal attachment • Garden path sentences (Rayner & Frazier, ‘83) The spy saw the cop with a telescope. minimal attach Build this structure first non-minimal attach Build this structure first

48. Modular prediction Lexical/semantic information rules this one out Interactive prediction Minimal attachment • Garden path sentences (Rayner & Frazier, ‘83) The spy saw the cop with a revolver. minimal attach Build this structure first non-minimal attach Build this structure first

49. S S NP VP NP the spy V NP VP S’ S’ the spy saw NP PP V PP NP the cop P NP saw P NP with the revolver but the cop didn’t see him the cop but the cop didn’t see him with the revolver MA Non-MA The spy saw the cop with the binoculars.. The spy saw the cop with the revolver … (Rayner & Frazier, ‘83) <- takes longer to read

50. evidence typically gets examined, but can’t do the examining Interactive Models • Other factors (e.g., semantic context, co-occurrence of usage & expectation) may provide cues about the likely interpretation of a sentence • Trueswell et al (1994) • The evidence examined by the lawyer … • The defendant examined by the lawyer…