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...
Autores principales: | , |
---|---|
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 |