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Description: Over the past decade, researches have begun to model the development of early vocabularies as network that acquire new nodes (words) over time. For these models to accurately predict word learning, the connectivity of the network should reflect the child's environment. In this work, we use a word assocation task with modified instructions to inform network connectivity. This network predicts word learning between 16 and 30 months better than a standard word association task.