Area:
Education and Early Childhood
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High-probability grants
According to our matching algorithm, Sarah D. Sahni is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2006 — 2008 |
Sahni, Sarah Devi |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
When Cues Converge: Multiple Regularities in Language Acquisition @ University of Wisconsin Madison
[unreadable] DESCRIPTION (provided by applicant): The goal of this research project is to employ behavioral and computational methods to better understand how infants use multiple regularities when learning language. Many researchers have posited that infants use statistical learning mechanisms to extract these regularities. However, the majority of this work focuses on infants' abilities to exploit a single regularity. In their natural environment, infants receive input that contains many overlapping regularities of varying consistency. Little research has focused on how infants process this type of input. In order to make use of the cues available in natural input, infants must be able to exploit these overlapping probabilistic regularities. The first aim of this grant is to explore how infants use multiple regularities to find words in fluent speech. By 9 months, infants are able to robustly use both lexical stress and sequential statistics to segment words. However, prior research has focused on how infants use these regularities in isolation, or how weighting of the cues changes developmentally. We hypothesize that infants can use these cues for word segmentation when they are probabilistic and overlapping, as they are in natural languages such as English. The second aim is to investigate the effect of multiple regularities on word learning. As a child's vocabulary grows, regularities arise among the labels and referents they know, as well as within the mappings between labels and referents. These regularities may affect the acquisition of new words. However, their potential role in subsequent word learning has not been carefully explored. Using computational models, we can examine these issues by carefully controlling regularities that exist within a vocabulary and by exploring how different types of regularities may affect word learning. These models can lead to a deeper understanding of these processing mechanisms and to novel predictions, which can then be tested in behavioral experiments. [unreadable] Public Health Interests: The goal of this research is to better understand how typically developing infants learn language - in particular, how they use the many patterns that exist in natural languages to do so. The ability to make use of multiple regularities likely affects infants' skills at language learning. By better understanding how this process unfolds in typically developing infants, researchers will be able to investigate how children with language delays and disabilities may differ in their ability to integrate multiple cues. In the future, this information will be useful for developing treatment plans. [unreadable] [unreadable] [unreadable]
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