differences in production account for differences in perception: the gradual learning algorithm...
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Differences in production account for differences in perception:
The Gradual Learning Algorithm predicts language-specific cue weighting
Paul Boersma, University of Amsterdam
Paola Escudero, University of Reading
Lisbon, February 2, 2001
Sound Contrasts
Sound contrasts and acoustic information An example of a sound contrast in English
What are the acoustic differences between the two?
Acoustic cues to “sheep” vs. “ship”
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Duration (ms)
Elspeth and Liz’s production environments
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Duration (ms)
E /I/
E /i/L /I/
L /i/
Do Elspeth and Liz perceive [350 Hz, 80 ms] as “sheep” or as “ship?
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Duration (ms)
?
E /I/
E /i/L /I/
L /i/
Why using the nearest production prototype in perception?
Why not perceiving it as an /e/ or an /o/?
Answer: “likelihood maximisation”, the most likely category
Functional principle: minimisation of perceptual confusion probability
How do Elspeth and Liz perceive the segments reliably?
[350 Hz,
80 ms]
350 Hz
not /I/
80 ms
not /i/
80 ms
not /I/
350 Hz
not /i/
/I/ *! *
/i/ * *
[350 Hz,
80 ms]
350 Hz
not /i/
80 ms
not /i/
80 ms
not /I/
350 Hz
not /I/
/I/ * *
/i/ *! *
How about baby Elspeth and baby Liz?
Little Elspeth and little Liz
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How about baby Elspeth and baby Liz?
Little Elspeth makes a mistake when categorising [350 Hz, 80 ms]
[350 Hz,
80 ms]
350 Hz
not /i/
80 ms
not /i/
80 ms
not /I/
350 Hz
not /I/
/I/ * *
/i/ *! *
Little Elspeth and little Liz have learned to perceive “sheep” and “ship” reliably”, they are adults
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Liz
Elspeth
Little Elspeth and little Liz have learned to perceive “sheep” and “ship” reliably”, they are adults
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Liz
Elspeth
The perception of real adult Elspeth and Liz
4.49 4.09
Elspeth
reliance 11%, weight 10%
[i]
[I]
[i ]
[I ]
5.2
3.71
Liz
reliance 32%, weight 30%
[i]
[I]
[i ]
[I ]