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Related Experiment Video

Updated: May 21, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Child-Directed Speech Facilitates Semantic Role Learning: A Machine Learning Approach.

Eva Huber^1,2, Balthasar Bickel¹, Sabine Stoll¹

¹Institute for the Interdisciplinary Study of Language Evolution, University of Zurich, Zurich, Switzerland.

Open Mind : Discoveries in Cognitive Science

|May 20, 2026

Summary

This summary is machine-generated.

Child-directed speech aids language acquisition by enhancing semantic role learning in both English and Russian. This specialized input helps children map meaning to syntax more effectively than adult-directed speech.

Keywords:

child-directed speech cross-linguistic neural language models semantic roles

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Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

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Related Experiment Videos

Last Updated: May 21, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

Area of Science:

Developmental psycholinguistics
Computational linguistics
Language acquisition

Background:

Semantic roles (agent, patient) are crucial for mapping meaning to syntax in language acquisition.
Child-directed speech (CDS) is a primary input source, but its effect on semantic role learning is understudied, especially in diverse languages.
English and Russian differ significantly in encoding semantic roles, presenting unique learning challenges.

Purpose of the Study:

To investigate if child-directed speech (CDS) facilitates semantic role learning compared to adult-directed speech (ADS).
To examine the impact of CDS on semantic role interpretation and generalization in English and Russian.
To analyze statistical properties of CDS and ADS using artificial neural language models.

Main Methods:

Utilized artificial neural language models to analyze naturalistic child-directed and adult-directed speech corpora in English and Russian.
Study 1: Assessed the ease of classifying semantic roles in CDS versus ADS utterances.
Study 2: Evaluated language models trained on CDS and ADS for their ability to learn and generalize semantic roles on a controlled test set.

Main Results:

Semantic roles were more easily classified in CDS than ADS, with a stronger effect observed in Russian.
Language models trained on CDS demonstrated superior learning and generalization of semantic roles compared to those trained on ADS, across both languages.
CDS appears optimized for languages with diverse semantic role expressions, like Russian, and supports generalization to novel structures.

Conclusions:

Child-directed speech is tailored to children's language-specific needs, actively facilitating semantic role acquisition.
Effective learning and generalization of semantic roles from CDS support the foundational mapping of meaning onto syntactic structure.
Findings provide the first evidence for CDS actively aiding semantic role acquisition, a prerequisite for syntax development.