Abstract
Recent technological advances and research trends have enabled the collection and analysis of multi-hour or daylong recordings of children's auditory environment. While this technology has allowed researchers to sample language experience from multiple contexts across the day, challenges remain with respect to how these audio recordings can or should be coded and analyzed. Daylong audio samples have the potential to transform our understanding of the language input that children encounter, but new analysis techniques may be necessary to take advantage of these new opportunities. The present work explores the linguistic content of the transcripts of three daylong recordings with the goal of understanding the content of these recordings in order to develop new ways to analyze and gain insight from these recordings.
Original language | English (US) |
---|---|
Pages | 3005-3011 |
Number of pages | 7 |
State | Published - 2020 |
Externally published | Yes |
Event | 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 - Virtual, Online Duration: Jul 29 2020 → Aug 1 2020 |
Conference
Conference | 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 |
---|---|
City | Virtual, Online |
Period | 7/29/20 → 8/1/20 |
Keywords
- corpus
- daylong audio
- language development
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Human-Computer Interaction
- Cognitive Neuroscience