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Are the products of statistical learning abstract or stimulus-specific?
Athena Vouloumanos1, Patricia E Brosseau-Liard, Evan Balaban
1Department of Psychology, New York University New York, NY, USA.
Frontiers in Psychology
|April 4, 2012
Summary
Statistical learning allows word segmentation from syllable streams. Representations formed are somewhat abstract, generalizing across some acoustic changes but limited by significant distortions.
Area of Science:
- Cognitive psychology
- Developmental linguistics
- Auditory perception
Background:
- Humans segment words from continuous speech using statistical learning.
- Transitional probabilities between syllables signal word boundaries.
- The nature of learned representations (abstract vs. stimulus-bound) is debated.
Purpose of the Study:
- To investigate the generalizability of representations formed through statistical learning.
- To determine if statistical learning yields abstract or stimulus-bound representations.
- To assess how acoustic variations affect the recognition of statistically segmented units.
Main Methods:
- Three experiments tested generalization of statistically segmented units.
- Stimuli included temporally reversed syllable streams and altered voices.
- Generalization was assessed across varying degrees of acoustic transformation.
Main Results:
- Learners recognized temporally reversed units (Experiment 1).
- Generalization from reversed streams was limited by mild acoustic transformation (Experiment 2).
- Voice changes allowed recognition, but mild distortion hindered it (Experiment 3).
Conclusions:
- Representations from statistical learning are abstract to a degree.
- Generalization is constrained by the extent of acoustic variability.
- Auditory learning representations are not entirely stimulus-bound but have limitations.
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