cuny 2013 handout

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This is a presentation slide that I used for my conference presentation at the 26th CUNY conference on sentence processing (Columbia, SC)

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1

Comprehension and acquisition of contrastive prosodyChigusa KurumadaMeredith BrownMichael. K. Tanenhaus

Identifying the speaker intention

A: Would you like some coffee?

B: I would love some caffeine.

A: (overlapping slightly with B’s answer) D’you take sugar -- Oh, you’d like some Pepsi?

2

Clark (2002)

Identifying the speaker intention

A: Would you like some coffee?

B: I would love some caffeine.

A: (overlapping slightly with B’s answer) D’you take sugar -- Oh, you’d like some Pepsi?

3

Clark (2002)

Bock & Levelt (1994)

coffee x other than coffee

“yes, please” “no, thank you”“I don’t drink coffee”

“I’d love some caffeine”“I’d love some CAFFEINE(L+H*)”

message component

lexicalgrammatical component

phonological component

output system

message component

lexicalgrammatical component

phonological component

output system

coffee

“I’d love some caffeine”

“I’d love some CAFFEINE(L+H*)”

x other than coffee

pragmatic intention

linguistic signal

i i

s

• lexicon• syntax• prosody

i = intention s = signal

“I’d love someCAFFEINE...”

“I’d LOVE somecaffeine”

pragmatic intention

linguistic signal

i

s s s

• lexicon• syntax• prosody

Our proposal

i

i = intention s = signal

8

P( i | s ) ∝ P ( s | i ) P ( i )

What intention does this signal convey?

How likely is s used when the intention

is i?

How likely is i to be conveyed?

i = intention s = signal

9

P( i | s ) ∝ P ( s | i ) P ( i )

i = intention s = signal

contextsignal

This talk

10

1. Inferential mappings in pragmatic interpretations of contrastive prosody

• Experiments 1- 4 with adults

2. Preschoolers’ comprehension

• Experiment 5 with 4-year-olds

(e.g., Cruttenden, 1985; Cutler & Swinney, 1987; Ito et al. 2013; Solan, 1980; Speer & Ito, 2009)

It looks like an X.

Noun-focus prosody Verb-focus prosody

“I think it is a zebra.” “but it is NOT one.”

11

12

intention

signal

It is an X It is not an X

“It looks like a ZEBRA!”

“It LOOKS like a zebra...”

P( i | s ) ∝ P ( s | i ) P ( i ) i = intention s = signal

13

P( i | s ) ∝ P ( s | i ) P ( i ) Exp. 1Exp. 2

Exp. 3

Exp. 4

cue reliability

prior expectations

Experiment 2: Cue Reliability

It is an X It is not an X

“It looks like a ZEBRA!”

“It LOOKS like a zebra...”

High-ReliabilityCondition

Low-ReliabilityCondition

P( i | s ) ∝ P ( s | i ) P ( i )

(contrastive prosody | “it is not an X”)

• High vs. Lowreliability

• 16 exposure(with feedback) 10 test(without feedback)

• N = 760.0

0.1

0.2

0.3

0.4

0.5

0.6

Reliable Unreliable

HighReliability

*p<.05

Prop

ortio

n of

“it

is n

ot a

n X

” re

adin

g

Noun-focus Verb-focus

0%

20%

40%

60%

LowReliability

17

P( i | s ) ∝ P ( s | i ) P ( i )

Exp. 3

Exp. 4

distributional learning(our poster, yesterday)

structural alternatives

Noun-focus Verb-focus

cue reliability

prior expectations

Exp. 1Exp. 2 ✓

Experiment 4: Structural alternatives

signal

intention

It is a zebra

“It LOOKS like a zebra...”

“It looks like a ZEBRA!”

It is not a zebra

Noun-focus Verb-focus

It is a zebra

“It looks like a ZEBRA!”

It is not a zebra

“It’s a ZEBRA!”

Noun-focus Verb-focus

speech signals

pragmatic intention

Experiment 4: Structural alternatives

“It LOOKS like a zebra...”

“It LOOKS like a zebra...”

“It is a ZEBRA!”

Noun-focus Verb-focus

speech signals

pragmatic intention

It is a zebra It is not a zebra

“It looks like a ZEBRA!”

Experiment 4: Structural alternatives

• N=48

• Test Phase only

• 24 2AFC questions(no feedback)

0.0

0.2

0.4

0.6

0.8

Control Target

Baseline with “it is an X”

Noun-focus Verb-focus

Control Target

8 Noun-focus

8 Verb-focus

8 It’s an X!

12 Noun-focus

Control

Experiment 4: Structural alternatives

12 Verb-focus

0.0

0.2

0.4

0.6

0.8

Control Target

Prop

ortio

n of

“it

is n

ot a

n X

” re

adin

gNoun-focus Verb-focus

Control with “it is an X”

0%

20%

40%

60%

80%

Experiment 4: Structural alternatives

23

P( i | s ) ∝ P ( s | i ) P ( i )

Exp. 3

Exp. 4

distributional learning(our poster, yesterday)

structural alternatives

cue reliability

prior expectations

Exp. 1Exp. 2

Acoustically identical items interpreted differently ✓

4-year-olds

24

n = 36, Average age = 4;7

Results

Prop

ortio

n of

“it

is n

ot a

n X

” re

adin

g

Combined4-year-olds

0%

20%

40%

60%

80%

100%

N-fo

cus

V-fo

cus

V-fo

cus

It’s

an X25

1. prosodic representations

3. finding alternative signals

2. pragmatic inferences

Difficulties may be in:

26

Prosody only Forms only Combined

8 Verb-focus

Conditions

8 Noun-focus

8 Noun-focus

8 Verb-focus

8 It’s an X 8 It’s an X

Prop

ortio

n of

“it

is n

ot a

n X

” re

adin

g

CombinedProsodyonly

Formsonly

0%

20%

40%

60%

80%

100%

N-fo

cus

V-fo

cus

N-fo

cus

It’s

an X

V-fo

cus

It’s

an X27

4-year-olds

ConclusionReliable intonational interpretation employs inferences between linguistic signals and speaker meanings.

28

i

s s s

i

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