on the processing of “ might ”
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On the PROCESSING of “ might ”. PLC 36. Dimka Atanassov, Florian Schwarz & John Trueswell. University of Pennsylvania. Literal vs. Pragmatically enriched meaning. Did Mary eat the cookies? (1) Mary ate some of the cookies a. Mary ate some, but not all of the cookies - PowerPoint PPT PresentationTRANSCRIPT
On the PROCESSING of “might”Dimka Atanassov, Florian Schwarz & John Trueswell
University of Pennsylvania
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PLC 36
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
Literal vs. Pragmatically enriched meaning
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Did Mary eat the cookies? (1) Mary ate some of the cookies a. Mary ate some, but not all of the
cookies b. In fact, Mary ate all of them (Grice, 1975): speakers are expected to
be as informative as necessary, but no more than that (quantity maxim).
Implicatures and scales
Mary ate some of the cookies Some and possibly all (literal) Some but not all (pragmatically enriched)
Would you happen to know where Mary is?
(2) Mary might be in her office
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Quantity
none some all might must
Certainty
Gadzar (1979) and Horn (1972
Visual world paradigm
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Previous psycholinguistics work: evidence for delayed implicatures
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Huang & Snedeker (2011) : Evidence for delayed implicature processing (600ms)
Point to the girl that has [some/two/all/three] of the ice cream sandwiches.
Some Two
target
distractor
target
distractor
target
distractor
target
distractor
all three
Previous psycholinguistics work: evidence for immediate implicatures
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Grodner et al. (2010): some is processed immediately.
Degen & Tanenhaus 2012: speed of computing some impl. depends on naturalness of some and its lexical alternatives
Click on the girl who has summa the balls/ alla the balloons/nunna the items.
Early summa condition Late summa condition
no way to identify target prior to phonological disambiguation.
summa target
summa target
More work on implicatures:
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Camp “Rapid” Camp “Delayed”Sedivy et al., 1999Degen & Tanenhaus 2012
Bott & Noveck, 2004Noveck & Posada, 2003 Huang & Snedeker, 2009a
Present study:
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Compares might to must instead of some to all
Instead of using prerecorded stimuli incorporates target utterances within a natural conversation with a confederate
A game of guessing with a confederate
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Subject and confederate take turns guessing shapes on a screen (Building on a design by Brown-Schmidt et al., 2008; Brown-Schmidt, 2009) Guesser: each time sees only part of the display
and has to guess whatever is hidden Verifier: sees entire display, including whatever is
hidden for the verifier, and has to mark guesses as “correct” or “incorrect”
Part I: subject guesses; Part 2: confederate guesses
Target sentences incorporated as part of the confederate’s “guesses”.
The game-rules:
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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4 types of shapes 4 possible colors In each row either
all shapes are of the same type or all are different
In each column either all items have same color or all have different color Col: all
different colors
Col: all same colors
Row: all different shapes
Example of a target trial
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Two conditions for every scene:confederate utters (1) followed by (2a) or (2b)1. Hmm…in the upper left there is a red square.2a.There must be a red square located in the upper right.2b. There might be a red square located in the bottom left.
Target
Competitor
Example of an “incorrect guess”
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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½ target items had guesses for “might” that happened to be incorrect (but consistent with rules)
There must be a green square located in the upper right. There might be a green square located in the bottom left. (but in reality it’s a green heart)
There must be a green square located in the upper right. There might be a green square located in the bottom left. (but in reality it’s a green heart)
Procedure
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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14 subjects, all native English speakers and undergraduates at UPenn participated for course credit (2 were taken out due to high track loss)
Stimuli presented in Experiment Builder Eye tracking data collected in Eyelink 1k
eye tracker Sampling rate: 1 kHz, re-sampled offline
to 100Hz
Results:
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
14Target Advantage for entire sentence (500ms prior to modal onset until 2 sec after onset of right/left)
Modal onset1s after mo
There must be a red square located in the upper right might bottom left
Avg. disambiguati
ontime
Target Advantage: looks to target- Looks to competitor.Target= shape that can be guessed with certainty (must)Competitor= shape that cannot be guessed with certainty (might)
Target Advantage: looks to target- Looks to competitor.Target= shape that can be guessed with certainty (must)Competitor= shape that cannot be guessed with certainty (might)
Results (continued):
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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A B
Ambiguity period: from modal onset (marked as 0) until 200ms after disambiguation (onset of upper right/ bottom left)
Significant interaction between condition and time window :by item p <.01; by subject p <.05
Correct Guesses, Ambiguity period
Interpretation: Implicature processing is
delayed by 800ms
Interpretation: Implicature processing is
delayed by 800ms
Conclusion
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Evidence for delayed processing times of scalar implicatures (800ms)
Comparable to previous results on all vs some (Huang & Snedeker)
Evidence based on different implicature triggers (must &might) using natural discourse context
Dimka Atanassov, Florian Schwarz and John Trueswell, UPenn PLC 36
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Thank You!
And many thanks to our confederates, Aviad Eilam and David Faber!