Predicting the birth of a spoken word
By Brandon Cain Roy, Michael C. Frank, P. DeCamp, Matthew Miller, Deb K. Roy. 2015
184 citations recorded by the source corpus.
Significance The emergence of productive language is a critical milestone in a child’s life. Laboratory studies have identified many individual factors that contribute to word learning, and larger scale studies show correlations between aspects of the home environment and language outcomes. To date, no study has compared across many factors involved in word learning. We introduce a new ultradense set of recordings that capture a single child’s daily experience during the emergence of language. We show that words used in distinctive spatial, temporal, and linguistic contexts are produced earlier, suggesting they are easier to learn. These findings support the importance of multimodal context in word learning for one child and provide new methods for quantifying the quality of children’s language input. Children learn words through an accumulation of interactions grounded in context. Although many factors in the learning environment have been shown to contribute to word learning in individual studies, no empirical synthesis connects across factors. We introduce a new ultradense corpus of audio and video recordings of a single child’s life that allows us to measure the child’s experience of each word in his vocabulary. This corpus provides the first direct comparison, to our knowledge, between different predictors of the child’s production of individual words. We develop a series of new measures of the distinctiveness of the spatial, temporal, and linguistic contexts in which a word appears, and show that these measures are stronger predictors of learning than frequency of use and that, unlike frequency, they play a consistent role across different syntactic categories. Our findings provide a concrete instantiation of classic ideas about the role of coherent activities in word learning and demonstrate the value of multimodal data in understanding children’s language acquisition.
Subfields: Artificial Intelligence, Developmental and Educational Psychology, Cognitive Science & Psychology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Tal Linzen
- Yonatan Belinkov
- Yoav Goldberg
- Samuel R. Bowman
- Ellie Pavlick
- R. Thomas McCoy
- Thomas Wolf
- Alex Warstadt
In Developmental and Educational Psychology
In Cognitive Science & Psychology
Citations in the corpus
- How Can We Accelerate Progress Towards Human-like Linguistic Generalization? (2020, background): “An analysis of recordings taken in the environment of the child of an MIT professor between the ages of 9 and 24 months found that the child heard or produced approximately eight million words over this 15-month period (Roy et al., 2015).”