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Statistical Cues in Language Acquisition: Word Segmentation by Infants

Abstract

A critical component of language acquisition is the ability to learn from the information present in the language input. In particular, young language learners would benefit from leaming mechanisms capable of utilizing the myriad statistical cues to linguistic structure available in the input. The present study examines eight-month-old infants' use of statistical cues in discovering word boundaries. Computational models suggest that one of the most useful cues in segmenting words out of continuous speech is distributional information: the detection of consistent orderings of sounds. In this paper, we present results suggesting that eight-month-old infants can in fact make use of the order in which sounds occur to discover word-like sequences. The implications of this early ability to detect statistical information in the language input will be discussed with regard to theoretical issues in the field of language acquisition.

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