Abstract—

A recent report demonstrated that 8-month-olds can seg-ment a continuous stream of speech syllables, containing no acoustic or prosodic cues to word boundaries, into wordlike units after only 2 min of listening experience (Saffran, Aslin, & Newport, 1996). Thus, a powerful learning mechanism capable of extracting statistical informa-tion from fluent speech is available early in development. The present study extends these results by documenting the particular type of statis-tical computation—transitional (conditional) probability—used by infants to solve this word-segmentation task. An artificial language corpus, consisting of a continuous stream of trisyllabic nonsense words, was presented to 8-month-olds for 3 min. A postfamiliarization test compared the infants ’ responses to words versus part-words (tri-syllabic sequences spanning word boundaries). The corpus was con-structed so that test words and part-words were matched in frequency, but differed in their transitional probabilities. Infants showed reliabl