Many studies have demonstrated that the amount of speech children receive is related to their vocabulary and language development: typically, the more speech, the better. In addition to quantity, other characteristics of child-directed speech are positively related to language development. The proposed research examines two of these characteristics: variation sets and contingent timing. Variation sets are clusters of related sentences with partial variation in form, such as """"""""Roll the ball. Can you roll the ball? Let's roll it."""""""" Contingent speech occurs when parents talk about an object on which their child's attention is focused. The goal of the proposed interdisciplinary research is to discover how children make use of these characteristics of child-directed speech. What underlying learning mechanisms are responsible for the facilitative effects of variation sets and contingent timing on language acquisition? The answer to this question will help explain the positive relation between the amount of speech directed to children and their language growth. The investigators integrate linguistics, computer science, and developmental psychology to study the contributions of variation sets and contingency in child-directed speech to early language acquisition. Their research will combine naturalistic yet tightly controlled word learning studies in young children with advanced computational modeling to elucidate mechanisms of socially embedded learning of nouns and verbs. The first goal of the research is to assess the effects on noun and verb learning of three properties of child-directed speech: a) the presence of variation sets, b) the time lag between utterances within variation sets, and c) the contingency of variation sets on the child's focus of attention. The second goal is to model the possible learning mechanisms that make use of these three properties. The investigators will use a Spike Timing Dependent Plasticity (STDP) model, which is a biologically plausible variety of the Hebbian learning rule that governs connectivity within neural assemblies. The computational model will receive input structured by the same parameters that facilitate learning in the behavioral experiments. Thus, a population of simulated learners will be created whose language learning performance will be directly comparable to that of human children. Mechanisms identified by STDP modeling will help explain how caregiver behavior assists children in tuning neural assemblies to sequences of speech stimuli. Taken together, the proposed studies will, for the first time, allow connections to be made between social interaction, neural organization, and language learning. By illuminating mechanisms by which infants and children learn from caregivers, the findings could inform interventions for disordered language development and help design more effective approaches to second-language instruction.
By illuminating mechanisms by which infants and children learn language from specific features of caregivers'child-directed speech, the findings could inform interventions for disordered language development. The results could also be used to help parents and early child educators create social environments that foster and support language growth. Eventually, this research could be used to design more effective approaches to second-language instruction.
