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From perception to categorization and back again… 8/29

From perception to categorization and back again… 8/29. 1. A Short Reprise… Categories Treating variable stimuli equivalently… Exemplars A particular perceptual occurrence of a category. 2. A Short Reprise… Perceptual Categorization Continuous perceptual input Discrete Categories. 3.

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From perception to categorization and back again… 8/29

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  1. From perception to categorization and back again… 8/29 1

  2. A Short Reprise… • Categories • Treating variable stimuli equivalently… • Exemplars • A particular perceptual occurrence of a category. 2

  3. A Short Reprise… Perceptual Categorization Continuous perceptual input Discrete Categories 3

  4. boundary Within-category variation Between category variation • Exemplars Vary • Category Boundaries • Between vs. Within Category variation • … on same dimension Cup Bowl 4

  5. Example: Speech Categories Why study speech? • Highly meaningful categorization. • Difficult categorization: lots of variation between speakers, speaking rates, phonation types • Difficult categorization: must happen very fast. • We understand the input well (from linguistics & phonetics) • Perhaps uses same principles as other types of categories. 5

  6. Example: Speech Categories • What’s discrete? • What’s continuous? • How is this mapping formed? 6

  7. Discrete Speech Categories • What is discrete? • Phonemes: Minimal contrastive unit. • Features: Voicing, Place, Manner • What is the relevant continuous perceptual detail? • How does this mapping take place? • What are the computations? 7

  8. frequency amplitude Continuous Speech Cues 1) What’s continuous? Not correlated with categories. More abstract cues? Frequency & Amplitude? 8

  9. formants frequency time At what frequencies is there energy at what time? amplitude frequency Speech is also temporal: changes over time. 9

  10. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 1 10

  11. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 2 11

  12. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 3 12

  13. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 4 13

  14. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 5 14 .25

  15. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 6 15

  16. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 7 16

  17. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 8 17

  18. Continuous Speech Cues VOT: Time difference between opening of oral release (lips/tongue) and onset of voicing. Voicing: B vs. P D vs. T K vs. G 9 18

  19. Continuous Speech Cues Formant Transition: Slope of formant frequency at word onset. Place: D vs. B vs. G S vs. Th vs. Sh 19

  20. Continuous Speech Cues Formant Transition: Slope of formant frequency at word onset. Place: D vs. B vs. G S vs. Th vs. Sh 20

  21. 2nd Formant Transition Voice Onset Time Continuous cues. How are they categorized into features and phonemes? How can we test hypothesized cues? Speech Continuum. 21

  22. Ba Da Ga Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Systematically vary 2nd formant from one end point to another… How do subjects identify each token? 22

  23. Ba Da Ga Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Synthetic speech: Pattern Playback Random order of tokens 3AFC 25 Reptitions x step x subject 23

  24. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Very consistent identification. 24

  25. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Does categorization affect perception? continuous input to discrete categories 25

  26. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Does categorization affect perception? Test discrimination within vs. between categories… ABX Task: Match third token to 1st or 2nd. 141 Within Same distance on continuum. Between 477 26

  27. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) • Randomized order. • Counterbalanced: X=A | X=B • ABX before and after labeling. • Does categorizing sounds affect discrimination? • Predicted scores based on identification only. 27

  28. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) 28

  29. Within-category Between-category Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Discrimination is not uniform across the continuum. Some comparisons are really hard. Some are easy. 29

  30. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Categorical Perception: 1) Sharp categorization. 2) Discrimination poor within category. 3) Discrimination good between categories. 30

  31. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) 1 2 3 4 5 6 7 8 9 10 Continuous cues can be thought of as a dimension or psychological space. 3 - 2 <<<< 6 - 5 In a normal space, distance is the same everywhere. CP warps this space. 31

  32. tall short tall short Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Categorical Perception 32

  33. three-step two-step one-step Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) If perception was continuous: discrimination should only depend on distance in continuous measure. D G Discrimination = f( distance) 33

  34. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) If perception was categorical: discrimination should only depend on distance in continuous measure. three-step two-step one-step D G Discrimination = f( location ) 34 .5

  35. Categorical Perception: Liberman, Harris, Hoffman & Griffith (1957) Actual Results: Discrimination is a combination of both. three-step two-step one-step D G Discrimination = f( distance and location ) True CP: = f( location ) 35 .5

  36. Is discrimination truly categorical? 1) Some effect of distance, but didn’t assess many “distances” 2) ABX Task is hard: converging evidence from 2nd task. 36

  37. 1) Assessing Distances Psychophysics: assess discrimination at a large numbers of stimulus differences. 100% Discrimination Gives complete picture of discrimination. 0% 0 300 600 900 1200 1500 1800 2100 2400 2700 3000 Frequency Difference 37

  38. 1) Assessing Distances Liberman et al assessed only 3 distances! 38

  39. 2) ABX Task and Difficulty ABX task requires listener to remember 3 things before making decision. • STM more efficient if items are chunked (G. Miller) • Syllables more efficient representation than raw acoustic form. • Subjects more likely to remember syllables. • Comparisons between syllables should be easier… • …Categorical Perception! 39

  40. 2) ABX Task and Difficulty Does the 3rd color match the 1st or 2nd? Task makes a huge difference. 1 2 ABX 40

  41. 2) ABX Task and Difficulty Does 1st color match left or right? Task makes a huge difference. 3 X[AB] 41

  42. 2) ABX Task and Difficulty Does 1st color match left or right? Task makes a huge difference. 3 X[AB] 42

  43. 2) ABX Task and Difficulty Are the two colors same or different? Task makes a huge difference. 5 6 AX 43

  44. 2) ABX Task and Difficulty Are the two colors same or different? Task makes a huge difference. 7 [AX] 44

  45. 2) ABX Task and Difficulty Are the two colors same or different? Task makes a huge difference. 8 [AX] 45

  46. continuous categorical Within-category Discrimination? • Carney, Widden, Viemeister (1977) • Examine CP with range of tasks. • Examine CP with a range of stimuli. Category boundary 100% Discrimination Sample Data 0% 0 60 10 20 30 40 50 -40 -50 -20 -10 Comparison Base Voice Onset Time 46

  47. Step 1: compute category boundaries. 2 AFC Identification. 47

  48. Do we see within-category discrimination in a range of tasks? • Experiment 1 • Same/Different Task: YES • Training: Even better. 48

  49. Do we see within-category discrimination in a range of tasks? • Experiment 2 • Oddity XAA, AXA or AAX YES • 3steps (30ms) between tokens. 49

  50. Do we see within-category discrimination in a range of tasks? • Experiment 3 • Same different with fixed anchor: VERY GOOD 50

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