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Language and Thought Lecture 2 Whorf Categorical Perception Statistics.

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2 Language and Thought Lecture 2 Whorf Categorical Perception Statistics

3 Benjamin Whorf Died at 44. Born Winthrop, MA MIT Chem. E. Fire Prevention Engineer Interest in Linguistics First Paper Nahuatl Nahuatl Aztec Yale E. Sapir Fieldwork Arizona – ModernNahuatl Yale: Research Fellowships Lecturer Introduction to Linguistic Relativity

4 Whorfian Hypothesis (Sapir-Whorf Hypothesis) Whorf (1956, p. 213): The categories and types that we isolate from the world of phenomena we do not find there because they stare every observer in the face; on the contrary, the world is presented as a kaleidoscopic flux of impressions which has to be organized by our minds – and this means largely by the linguistic systems in our minds.

5 Terminologies Linguistic Determinism (strong) Linguistic Determinism (strong) Linguistic Relativity (weak) Linguistic Relativity (weak)

6 Whorf as a fire prevention engineer Observation: Many fires are started because of terrible language. Observation: Many fires are started because of terrible language. –E.g. carelessness around “Empty” gasoline drums. “Empty”  ok to flick cigarette butt Empty-looking  “Empty”  ok to flick cigarette butt Thought  Language/Behavior. Language  Thought/Behavior.

7 Whorf’s argument Argument Argument –Languages vary in their conceptual repertoire. –Thought is dependent on language. –Thus, speakers of different languages think differently. Evidence? Evidence? –Languages vary! FIX: Need separate measure of thought!

8 Another problem? Suppose it is true that Suppose it is true that 1.Eskimos make fine discriminations of snow, and Americans do not. 2.Eskimos have more words for snow than Americans – Now what’s the cause & effect? Eskimos make fine snow discriminations BECAUSE they have lots of snow words. Eskimos make fine snow discriminations BECAUSE they have lots of snow words.OR Eskimos learn to make fine snow discriminations AND SO they have lots of snow words. Eskimos learn to make fine snow discriminations AND SO they have lots of snow words. Now how do you tease things apart???

9 Dissociating language and circumstance Move Americans to Vail or Aspen Move Americans to Vail or Aspen ‘sugar’‘granule’‘powder’ Move Eskimos to Bermuda Move Eskimos to Bermuda

10 Experiments in various domains Some examples: Color Color Object Object Space Space Time Time Number Number Theory of Mind Theory of Mind

11 People who grew up without learning language. Infants who have not learned language. Animals who do not speak a language. Subject Population Speakers of another language. Aphasics: patients who suffered brain damage leading to language problems.

12 Color

13 Ring ON Pole Cup ON Saucer Telephone ON Wall Lady ON TV Moustache ON Face Spatial Prepositions IM? UM? AUF? AN? IM?

14 “Where is the girl?” –The girl is south of the umbrella. –The girl is at the tilted side of the umbrella. –The girl is to the left of the umbrella. Figure Reference Object Spatial Frames of Reference

15 Reorientation “Left of the blue wall”

16 Number Piraha: “one-two-many” counting system.

17 Theory of Mind

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19 What is categorical Perception?

20 Frequency (Hz) Time (msec) bada ga What is Categorical Perception? Example of Categorical Perception

21 Speaking Vocal Tract: Vocal Fold  Lips (Modeled as a tube) Vocal Fold Lips Average Man - Length = 17.4cm

22 Vocal Tract Model F1 F2 F3 Vocal Tract = 17.4 cm Speed of sound = cm/sec Speed = Distance/Time = Wavelength x Frequency Freq = Speed/Wavelength L = 17.4cm 500Hz 1500Hz 2500Hz λ = 4L λ = 4L/3 λ = 4L/5

23 Speaking c d a b c d ab on top of his deck Vocal folds Lips

24 Vocal Tract ee oo oh ah eh

25 Spectrogram Time  frequency

26 Pattern Playback Machine

27 Spectrogram Steady State Steady State Transitional State Transitional State

28 Methods for Testing Categorical Perception Identification Identification –Randomly play the audio clips and asked to identify the phoneme Discrimination Discrimination –Randomly play pairs and asked to make Same-different Judgment Same pairs Same pairs Different pairs Different pairs

29 Identification Identification Identification –Randomly play the audio clips and asked to identify the phoneme If there is CP, what should the graph look like? If there is CP, what should the graph look like? –X-axis stimuli arranged in a continuum with very small incremental difference between the stimuli –Y-axis % Identification as the tested category

30 Identification (idealized results) % Identification as Category X Stimulus # 17

31 Frequency (Hz) Time (msec) bada ga What is Categorical Perception?

32 Categorical Perception (Idealized Data)

33 Methods for Testing Categorical Perception Identification Identification –Randomly play the audio clips and asked to identify the phoneme Discrimination Discrimination –Randomly play pairs and asked to make Same-different Judgment Same pairs Same pairs Different pairs Different pairs

34 Discrimination Study Last example of ba/da/ga varied transitional state (up, down of F2). Last example of ba/da/ga varied transitional state (up, down of F2). In this example, Varying Voice Onset Time. In this example, Varying Voice Onset Time.

35 Voice Onset Time (VOT) VOT: VOT: time between consonant release and vocal cord vibration [p] [b] So what is the difference in VOT between VOICELESS [b] and VOICED [p]? So what is the difference in VOT between VOICELESS [b] and VOICED [p]? –SHORT VOT  voiced –LONG VOT  voiced

36 Voice Onset Time (VOT) Short VOT = ? Short VOT = ? Long VOT = ? Long VOT = ? Which one is /di/ and which one is /ti/? Which one is /di/ and which one is /ti/? diti

37 Discrimination Study Same/Different? 0ms 60ms Same/Different? 0ms 10ms Same/Different? 40ms Why is this pair difficult? (i) Acoustically similar? (ii) Same Category?

38 Discrimination Same/Different 0ms 60ms Same/Different 0ms 10ms Same/Different 40ms A More Systematic Test 0ms 20ms 40ms 20ms 40ms 60ms DT D T T D Within-Category Discrimination is Hard

39 Categorical Perception (Idealized Discrimination Data) % Correct Discrimination Pairs by VOT

40 Question 1 Is speech perception innate? Is speech perception innate? –Do newborns have categorical perception? If CP requires exposure to language (e.g., knowledge of minimal pairs in one’s language), then NO. If CP requires exposure to language (e.g., knowledge of minimal pairs in one’s language), then NO. If CP is innate, then YES. If CP is innate, then YES. –How do we test newborns?

41 High Amplitude Sucking Procedure Infant given a pacifier that measures sucking rate Infant given a pacifier that measures sucking rate Habituation – Infant sucks to hear sound (e.g. ba) until bored. Habituation – Infant sucks to hear sound (e.g. ba) until bored. Test – Play sound (e.g., ba or pa). Is there dishabituation? Test – Play sound (e.g., ba or pa). Is there dishabituation? –Infants will suck to hear sound if the sound is no longer boring. (2:50 min. into videoclip)

42 Stimuli for Eimas et. al’s Study BA vs. PA BA vs. PA Vary Voice Onset Time (VOT): time btw consonant release and vocal cord vibration Vary Voice Onset Time (VOT): time btw consonant release and vocal cord vibration VOT in milliseconds PA BA

43 Predictions Between Category BA 1 -PA Within Category BA 1 -BA 2 Within Category Control BA 1 -BA 1 Innate Categorical Perception dishabituate remain habituated Untuned Sensitivity dishabituatedishabituate remain habituated Insensitive BA 1 = VOT 20ms; BA 2 = VOT 0ms; PA = VOT 40ms

44 Results for Eimas et. al’s Study MEAN NUMBER OF SUCKING RESPONSE dishab no

45 Question 1 Answer Q1: Is Speech Perception Innate? Many other studies since tested: Many other studies since tested: –Infants (Neonates) on other contrasts. Consensus: Yes to Innate Q. Consensus: Yes to Innate Q. –Infants do not discriminate all physically equal acoustic difference; they show heightened sensitivity to those that are important for language. –BUT… there is language-specific fine-tuning…

46 Provisional Conclusions Speech Perception makes use of some auditory mechanisms which evolved prior to language Speech Perception makes use of some auditory mechanisms which evolved prior to language –These abilities are innate

47 Becoming a Native Listener Languages differ in their inventories of phonemes. Languages differ in their inventories of phonemes. What develops or changes in our speech perception abilities? What develops or changes in our speech perception abilities? Language Specific Fine Tuning

48 Japanese vs. English (Miyawaki et al. 1975) RA LA AMERICANS

49 Dental Stop – tip of tongue touching back of front teeth Retroflex Stop – tongue curled so tip is behind alveolar ridge Hindi (spoken in India) unvoiced unaspirated retroflex vs. dental stop (English /t/ is typically somewhere between the two)

50 Can you hear the difference? Hindi dental retroflex

51 Uvular – tongue is raised against the velum Velar – tongue is raised behind the velum Salish (Native North American language): glotalized voiceless stops (they are actually ejectives - ejective is produced by obstructing the airflow by raising the back of the tongue against or behind the velum)

52 When does changes in sensitivity occur? Infancy Adulthood … And testing method?

53 Conditioned Head-Turn Conditioning Conditioning –Child hears a string of sounds. –Conditioned to turn head when detects a change (e.g., bell  whistle) with reward Test Test –Speech sounds (e.g., da, da, da, da, ta,…) –Does the child turn his or her head with changed from da to ta? Werker: Kuhl:

54 When does Change Occur? 6-8m 8-10m 10-12m11-12m 6-8m 8-10m 10-12m11-12m

55 What is changing? Two contrasting views: 1 or 2? Maintenance or Loss Maintenance or Loss –If you don’t use it, you lose it. –Parallel aspects of early visual development. Functional Reorganization Functional Reorganization –Existing architecture reorganized for higher level of processing.

56 What is changing? Two contrasting views

57 What is changing? 1. Maintenance or Loss View Structure- changing Non-native boundaries disappear. Resulting in native language phonetics Phonetics Acoustics Phonology

58 What is changing? 2. Functional Reorganization Structure- building Native language phonemes built from universal phones Phonetics Acoustics Phonology

59 Which view? Werker (1997) noted some problems for the maintenance or loss view. Werker (1997) noted some problems for the maintenance or loss view. 1. Many of the uncategorized sounds do appear in the native language but just are not meaningful (e.g., as allophones), and speakers can be made aware of the difference. Example: –/p/ is only aspirated in “pin” and not “spin’ –/p/ in “pin” and “spin” are allophones in English –But could be minimal pairs in some other languages.

60 Which view? Werker (1997) noted some problems for the maintenance or loss view. Werker (1997) noted some problems for the maintenance or loss view. 1. Many of the uncategorized sounds do appear in the native language but just are not meaningful (e.g., as allophones), and speakers can be made aware of the difference. 2. Children who fail to show categorical perception for non- native phonemes can acquire a new language without an accent. 3. Adults can be trained to make non-native distinctions. 4. Perceptual distinction is readily available for non-linguistic tasks. Language Specific Fine Tuning

61 Which model? Werker (1997): The evidence that poses problems for maintenance or loss view supports the functional reorganization view. Werker (1997): The evidence that poses problems for maintenance or loss view supports the functional reorganization view. I.e., the view that: I.e., the view that: –Those perceptual categories which are meaningful in the native language become speech categories. –The remainder are perceived but not recruited in speech perception. Language Specific Fine Tuning

62 Statistics

63 Outline Stats Terms Simplified Stats Terms Simplified –t-tests –ANOVAs, Main effects and Interactions –Regressions, Correlations

64 T-tests and ANOVAs T-tests: Compare 2 means. T-tests: Compare 2 means. ANOVA (Analysis of Variance): Compare multiple means ANOVA (Analysis of Variance): Compare multiple means –Yields significance of main or interaction effects

65 Hypothetical Experiment (Example of Main & Interactions Effects) Dependent Measure: Number of Girlfriends Dependent Measure: Number of Girlfriends Independent Measure: Independent Measure: –Wealth of bachelors according to Income (Rich, Poor) (Rich, Poor) –Looks of same bachelors according to Oprah (Handsome, Ugly) (Handsome, Ugly)

66 Design 2 x 2 RichPoor Hand-some Ugly # of GF

67 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) Is a female model more attractive in short or long skirt? Is a female model more attractive in short or long skirt? – Model pictured in 10 different short skirts and 10 different long skirts –30 Males rated the model’s attractiveness in each skirt (1 = not attractive to 7 = extremely attractive)

68 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) F1: Subject Analysis F1: Subject Analysis –Comparing subjects –Averaging across items for each subject F2: Items Analysis F2: Items Analysis –Comparing items –Averaging across subjects for each item

69 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) F1: Subject Analysis F1: Subject Analysis F2: Items Analysis F2: Items Analysis ShortLong Frederick H Hef Rudy G Bill C Rating Short Skirt 14.5 Short Skirt 25.3 … Long Skirt 16.7 Long Skirt 23.5 …


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