Assistant Professor Jessica Hay was recently awarded a 5-year $1.3 million dollar NIH R01 grant titled, "Infant statistical learning: Resilience, longevity, and specificity".
Assistant Professor Jessica Hay was recently awarded a 5-year $1.3 million dollar NIH R01 grant titled, "Infant statistical learning: Resilience, longevity, and specificity". This award is especially noteworthy in the current extraordinarily competitive national funding environment.
A brief abstract of Dr. Hay's exciting new research project:
Typically developing infants acquire language at a remarkable rate despite numerous perceptual and cognitive challenges. One specific challenge that infants face is finding words in speech that unfolds continuously with few reliable cues to words boundaries. Previous research suggests that infants possess powerful computational mechanisms that allow them to track regularities in their environment. It has been suggested that these computational mechanisms, often referred to as statistical learning mechanisms, may support infants' ability to find words in fluent speech and use the output of their statistical computations to facilitate subsequent word learning. However, in order to build a vocabulary, infants must also be able to identify words in complex and noisy listening environments, encode words into long-term memory, and remember words over time and in various contexts. Further, infants must represent words with the appropriate level of detail in their lexicons, attending to relevant cues (e.g., what consonants and vowels are in words) while ignoring irrelevant variations in the ways words are produced (e.g. male vs female voice). The problem is that there is little research on the extent to which statistical learning mechanisms support early language acquisition under these types of challenging learning conditions. The objective of the proposed research is to advance integrative and comprehensive theories of infant language acquisition by assessing how statistical learning supports (1) speech segmentation and word learning in background noise, (2) infants' abilities to encode recently segmented words in long-term memory, and (3) infants' abilities to represent newly segmented words with the appropriate level and type of detail to facilitate subsequent language learning. Results from the proposed project will advance our understanding of the learning mechanisms underlying normative language development. Individuals who are, for a variety of sensory, neurological, or developmental reasons, less adept at tracking and representing statistical regularities when faced with real-world learning challenges may be at greater risk for atypical language development. Results from the proposed research will be used to help generate and test hypotheses about the causal mechanisms for specific language delays in atypical populations, such as for infants with hearing loss or infants who, for various reasons, receive sub-optimal language input during critical developmental periods.