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Updated: Nov 19, 2025
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Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
Published on: February 8, 2019
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Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input
Thomas Schatz1,2, Naomi H Feldman3,2, Sharon Goldwater4
1Department of Linguistics, University of Maryland, College Park, MD 20742; thomas.schatz.1986@gmail.com.
Summary
Infants learn speech sounds early by processing native language patterns. A new model shows distributional learning predicts this attunement, but infants may not form traditional phonetic categories.
Area of Science:
- Cognitive Science
- Developmental Psychology
- Linguistics
Background:
- Infants attune to native language sounds before speaking.
- Early phonetic learning involves distinguishing native from non-native speech contrasts.
- Distributional learning was proposed as a mechanism for infants to form phonetic categories.
Purpose of the Study:
- To test if distributional learning can predict early phonetic learning in infants.
- To investigate the nature of units infants learn through distributional learning.
- To challenge the hypothesis that infants learn phonetic categories.
Main Methods:
- Developed a distributional learning algorithm for naturalistic speech.
- Applied the algorithm to predict infant phonetic learning patterns.
- Analyzed the acoustic properties of units learned by the model.
Main Results:
- The distributional learning model successfully predicted early phonetic learning in infants.
- The model learned units that were too brief and acoustically fine-grained for phonetic categories.
- Findings challenge the idea that infants learn discrete phonetic categories.
Conclusions:
- Distributional learning is a plausible mechanism for early phonetic learning.
- Infants may not form traditional phonetic categories but rather finer acoustic units.
- Introduced a mechanism-driven approach and quantitative framework for studying early phonetic learning.
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