Cargando…

Naturalistic speech supports distributional learning across contexts

At birth, infants discriminate most of the sounds of the world’s languages, but by age 1, infants become language-specific listeners. This has generally been taken as evidence that infants have learned which acoustic dimensions are contrastive, or useful for distinguishing among the sounds of their...

Descripción completa

Detalles Bibliográficos
Autores principales: Hitczenko, Kasia, Feldman, Naomi H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9499502/
https://www.ncbi.nlm.nih.gov/pubmed/36095175
http://dx.doi.org/10.1073/pnas.2123230119
_version_ 1784795006810193920
author Hitczenko, Kasia
Feldman, Naomi H.
author_facet Hitczenko, Kasia
Feldman, Naomi H.
author_sort Hitczenko, Kasia
collection PubMed
description At birth, infants discriminate most of the sounds of the world’s languages, but by age 1, infants become language-specific listeners. This has generally been taken as evidence that infants have learned which acoustic dimensions are contrastive, or useful for distinguishing among the sounds of their language(s), and have begun focusing primarily on those dimensions when perceiving speech. However, speech is highly variable, with different sounds overlapping substantially in their acoustics, and after decades of research, we still do not know what aspects of the speech signal allow infants to differentiate contrastive from noncontrastive dimensions. Here we show that infants could learn which acoustic dimensions of their language are contrastive, despite the high acoustic variability. Our account is based on the cross-linguistic fact that even sounds that overlap in their acoustics differ in the contexts they occur in. We predict that this should leave a signal that infants can pick up on and show that acoustic distributions indeed vary more by context along contrastive dimensions compared with noncontrastive dimensions. By establishing this difference, we provide a potential answer to how infants learn about sound contrasts, a question whose answer in natural learning environments has remained elusive.
format Online
Article
Text
id pubmed-9499502
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher National Academy of Sciences
record_format MEDLINE/PubMed
spelling pubmed-94995022023-03-12 Naturalistic speech supports distributional learning across contexts Hitczenko, Kasia Feldman, Naomi H. Proc Natl Acad Sci U S A Social Sciences At birth, infants discriminate most of the sounds of the world’s languages, but by age 1, infants become language-specific listeners. This has generally been taken as evidence that infants have learned which acoustic dimensions are contrastive, or useful for distinguishing among the sounds of their language(s), and have begun focusing primarily on those dimensions when perceiving speech. However, speech is highly variable, with different sounds overlapping substantially in their acoustics, and after decades of research, we still do not know what aspects of the speech signal allow infants to differentiate contrastive from noncontrastive dimensions. Here we show that infants could learn which acoustic dimensions of their language are contrastive, despite the high acoustic variability. Our account is based on the cross-linguistic fact that even sounds that overlap in their acoustics differ in the contexts they occur in. We predict that this should leave a signal that infants can pick up on and show that acoustic distributions indeed vary more by context along contrastive dimensions compared with noncontrastive dimensions. By establishing this difference, we provide a potential answer to how infants learn about sound contrasts, a question whose answer in natural learning environments has remained elusive. National Academy of Sciences 2022-09-12 2022-09-20 /pmc/articles/PMC9499502/ /pubmed/36095175 http://dx.doi.org/10.1073/pnas.2123230119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
Hitczenko, Kasia
Feldman, Naomi H.
Naturalistic speech supports distributional learning across contexts
title Naturalistic speech supports distributional learning across contexts
title_full Naturalistic speech supports distributional learning across contexts
title_fullStr Naturalistic speech supports distributional learning across contexts
title_full_unstemmed Naturalistic speech supports distributional learning across contexts
title_short Naturalistic speech supports distributional learning across contexts
title_sort naturalistic speech supports distributional learning across contexts
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9499502/
https://www.ncbi.nlm.nih.gov/pubmed/36095175
http://dx.doi.org/10.1073/pnas.2123230119
work_keys_str_mv AT hitczenkokasia naturalisticspeechsupportsdistributionallearningacrosscontexts
AT feldmannaomih naturalisticspeechsupportsdistributionallearningacrosscontexts