Bayesian Inference in Word Learning

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  • The fundamental task of word learning is to map the phonological sound of a word to its referent or extension in the world: to realize, for instance, that the phoneme sequence /dog/ maps onto Snoopy and Fido but not the neighbor's cat. This is a difficult problem because as the philosopher W. V. O. Quine (and many since) has demonstrated that the meanings of words are inherently logically underconstrained. There are an infinite number of possibilities consistent with the meaning of any word: Dog could mean four-legged animal that barks, undetached dog parts, this instance of a barking animal until time, furry animals 93 million miles from the sun, and so forth. In addition, children appear to learn words gradually, and even adults do not ...

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