The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
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Children can determine the meaning of a new word from hearing it used in a familiar context---an ability often referred to as fast mapping. In this paper, we study fast mapping in the context of a general probabilistic model of word learning. We use our model to simulate fast mapping experiments on children, such as referent selection and retention. The word learning model can perform these tasks through an inductive interpretation of the acquired probabilities. Our results suggest that fast mapping occurs as a natural consequence of learning more words, and provides explanations for the (occasionally contradictory) child experimental data.