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Integrating constraints for learning word-referent mappings

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>04/2012
Issue number1
Number of pages11
Pages (from-to)133-143
<mark>Original language</mark>English


Learning word-referent mappings is complex because the word and its referent tend to co-occur with multiple other words and potential referents. Such complexity has led to proposals for a host of constraints on learning, though how these constraints may interact has not yet been investigated in detail. In this paper, we investigated interactions between word co-occurrence constraints and cross-situational statistics in word learning. Analyses of child-directed speech revealed that when both object-referring and non-referring words occurred in the utterance, referring words were more likely to be preceded by a determiner than when the utterance contained only referring words. In a word learning study containing both referring and non-referring words, learning was facilitated when non-referring words contributed grammatical constraints analogous to determiners. The complexity of multi-word utterances provides an opportunity for co-occurrence constraints to contribute to word-referent mapping, and the learning mechanism is able to integrate these multiple sources of information.