Judging words by their covers and the company they keep: probabilistic cues support word learning

Abstract

Statistical learning may be central to lexical and grammatical development. The phonological and distributional properties of words provide probabilistic cues to their grammatical and semantic properties. Infants can capitalize on such probabilistic cues to learn grammatical patterns in listening tasks. However, infants often struggle to learn labels when performance requires attending to less obvious cues, raising the question of whether probabilistic cues support word learning. The current experiment presented 22-month-olds with an artificial language containing probabilistic correlations between words' statistical and semantic properties. Only infants with higher levels of grammatical development capitalized on statistical cues to support learning word-referent mappings. These findings suggest that infants' sensitivity to correlations between sounds and meanings may support both word learning and grammatical development.