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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| Veröffentlicht in: | Open mind (Cambridge, Mass.) Mass.), 2021-05, Vol.5, p.20-29 |
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| container_title | Open mind (Cambridge, Mass.) |
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| creator | Sullivan, Jessica Mei, Michelle Perfors, Andrew Wojcik, Erica Frank, Michael C. |
| 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. |
| doi_str_mv | 10.1162/opmi_a_00039 |
| format | Article |
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| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; PubMed Central Open Access; ProQuest Central |
| subjects | Access control Access to information Age Cameras child development Children & youth Datasets Families & family life first-person video headcam Metadata |
| title | SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective |
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