Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling

Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm-the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal information at all. Our results raise the possibility that early language discrimination may be independent of speech rhythm, and call for theoretical reconsideration of how infants learn suprasegmental information in the first few months of their lives. SUMMARY: We simulate newborn language discrimination with machine learning models on naturalistic speech stimuli. Models can discriminate between languages just like newborns, even when rhythmic information is removed. This means that infants' behavior could rely on their ability to perceive global properties of speech, rather than rhythm. Our results challenge theories of how newborns perceive speech, and how that shapes later language.

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Publication Details

Journal
Developmental Science
Published
2026-05-08
DOI
https://doi.org/10.1111/desc.70220
Primary Topic
Language Development and Disorders
Type
article
Field-Weighted Citation Impact
0.00

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article

Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling

Naomi H. Feldman, Ruolan Leslie Famularo, Ali Aboelata, Thomas Schatz
Developmental Science
Language Development and Disorders
article

Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling

Naomi H. Feldman, Ruolan Leslie Famularo, Ali Aboelata, Thomas Schatz
article en

Abstract

Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm-the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal information at all. Our results raise the possibility that early language discrimination may be independent of speech rhythm, and call for theoretical reconsideration of how infants learn suprasegmental information in the first few months of their lives. SUMMARY: We simulate newborn language discrimination with machine learning models on naturalistic speech stimuli. Models can discriminate between languages just like newborns, even when rhythmic information is removed. This means that infants' behavior could rely on their ability to perceive global properties of speech, rather than rhythm. Our results challenge theories of how newborns perceive speech, and how that shapes later language.

Developmental ScienceVol. 29(4)
Centre National de la Recherche Scientifique (FR), Aix-Marseille Université (FR), Laboratoire d’Informatique et Systèmes (FR), University of Maryland, College Park (US)
National Science Foundation
Reduced inequalities
Openalex Percentile: Top 5%
Language Development and Disorders
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Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling — Naomi H. Feldman, Ruolan Leslie Famularo, et al. · Developmental Science (2026) | TGRS Research Map | TGRS