Various infant studies suggest that statistical regularities in the speech stream (e.g. transitional probabilities) are one of the first speech segmentation cues available. Statistical learning may serve as a mechanism for learning various language specific segmentation cues (e.g. stress segmentation by English speakers). To test this possibility we exposed adults to an artificial language in which all words had a novel acoustic cue on the final syllable. Subjects were presented with a continuous stream of synthesized speech in which the words were repeated in random order. Subjects were then given a new set of words to see if they had learned the acoustic cue and generalized it to new stimuli. Finally, subjects were exposed to a competition stream in which the transitional probability and novel acoustic cues conflicted to see which cue they preferred to use for segmentation. Results on the word-learning test suggest that subjects were able to segment the first exposure stream, however, on the cue transfer test they did not display any evidence of learning the relationship between word boundaries and the novel acoustic cue. Subjects were able to learn statistical words from the competition stream despite extra intervening syllables.