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Creators/Authors contains: "Rane, S"

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  1. ; ; ; ; ; (, Proceedings of the Annual Meeting of the Cognitive Science Society)
    For human children as well as machine learning systems, a key challenge in learning a word is linking the word to the visual phenomena it describes. We explore this aspect of word learn- ing by using the performance of computer vision systems as a proxy for the difficulty of learning a word from visual cues. We show that the age at which children acquire different categories of words is correlated with the performance of visual classifi- cation and captioning systems, over and above the expected effects of word frequency. The performance of the computer vision systems is correlated with human judgments of the con- creteness of words, which are in turn a predictor of children’s word learning, suggesting that these models are capturing the relationship between words and visual phenomena. 
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