Learning words through probabilistic inferences about speakers’ communicative intentions
How do children learn the meanings of words? This chapter presents a probabilistic, communicative view of word learning that synthesizes insights from work on statistical learning and social learning. By describing the formal characteristics of models, it is possible to differentiate communicative models that make inferences about the speaker’s intentions from associative models that treat social information as a signal of salience. In addition, the probabilistic communicative framework can be integrated with models of pragmatic reasoning, leading to insights into how Gricean principles can facilitate word learning.
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Cited by 1 other publications
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Learning Maximum Absolute Meaning Through Reasoning About Speaker Intentions.
Language Learning 71:2
► pp. 326 ff.
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