SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective

We introduce a new resource: the SAYCam corpus. Infants aged 6–32 months wore a head-mounted camera for approximately 2 hr per week, over the course of approximately two-and-a-half years. The result is a large, naturalistic, longitudinal dataset of infant- and child-perspective videos. Over 200,000...

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Detalles Bibliográficos
Autores principales: Sullivan, Jessica, Mei, Michelle, Perfors, Andrew, Wojcik, Erica, Frank, Michael C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412186/
https://www.ncbi.nlm.nih.gov/pubmed/34485795
http://dx.doi.org/10.1162/opmi_a_00039
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author Sullivan, Jessica
Mei, Michelle
Perfors, Andrew
Wojcik, Erica
Frank, Michael C.
author_facet Sullivan, Jessica
Mei, Michelle
Perfors, Andrew
Wojcik, Erica
Frank, Michael C.
author_sort Sullivan, Jessica
collection PubMed
description We introduce a new resource: the SAYCam corpus. Infants aged 6–32 months wore a head-mounted camera for approximately 2 hr per week, over the course of approximately two-and-a-half years. The result is a large, naturalistic, longitudinal dataset of infant- and child-perspective videos. Over 200,000 words of naturalistic speech have already been transcribed. Similarly, the dataset is searchable using a number of criteria (e.g., age of participant, location, setting, objects present). The resulting dataset will be of broad use to psychologists, linguists, and computer scientists.
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spelling pubmed-84121862021-09-03 SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective Sullivan, Jessica Mei, Michelle Perfors, Andrew Wojcik, Erica Frank, Michael C. Open Mind (Camb) Research Article We introduce a new resource: the SAYCam corpus. Infants aged 6–32 months wore a head-mounted camera for approximately 2 hr per week, over the course of approximately two-and-a-half years. The result is a large, naturalistic, longitudinal dataset of infant- and child-perspective videos. Over 200,000 words of naturalistic speech have already been transcribed. Similarly, the dataset is searchable using a number of criteria (e.g., age of participant, location, setting, objects present). The resulting dataset will be of broad use to psychologists, linguists, and computer scientists. MIT Press 2021-05-26 /pmc/articles/PMC8412186/ /pubmed/34485795 http://dx.doi.org/10.1162/opmi_a_00039 Text en © 2021 Massachusetts Institute of Technology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Sullivan, Jessica
Mei, Michelle
Perfors, Andrew
Wojcik, Erica
Frank, Michael C.
SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title_full SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title_fullStr SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title_full_unstemmed SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title_short SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
title_sort saycam: a large, longitudinal audiovisual dataset recorded from the infant’s perspective
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412186/
https://www.ncbi.nlm.nih.gov/pubmed/34485795
http://dx.doi.org/10.1162/opmi_a_00039
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