Much of what we know about the development of listeners' word segmentation strategies originates from the artificial language-learning literature. However, many artificial speech streams designed to study word segmentation lack a salient cue found in all natural languages: utterance boundaries. In this study, participants listened to a speech-stream containing one of three sets of word boundary cues: transitional probabilities between syllables (TP Condition), silences marking utterance boundaries (UB Condition), or a combination of both cues (TP + UB Condition). Recognition of the trained words and rule words (words not in language, but conforming to its phonotactic structure) was tested. Participants performed equally well in the TP + UB and UB Conditions, scoring above chance on both trained and rule words. Performance in the TP condition, however, was at chance. Our results suggest that attention to UBs is a particularly effective strategy for finding words in speech, possibly providing a language-general solution to the word segmentation problem.