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Taking the child’s view: Syllable-based Bayesian inference as a (more) plausible statistical word segmentation strategy

By Lawrence Phillips and Lisa Pearl

Abstract

Because knowledge of words plays a crucial role in acquisition and children seem to accomplish word segmentation very early (~7.5 months (Jusczyk et al., 1999; Echols et al., 1997; Jusczyk et al., 1993a)), many strategies have been proposed for how children learn to identify words in their native language. Because of experimental evidence that infants are sensitive to statistical information in their environment (e.g. Saffran, Aslin & Newport, 1996) statistical strategies have seen a rise in popularity. Many recent statistical models of word segmentation have assumed one basic unit of representation available to the learner is the phoneme (e.g.

Year: 2013
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