Transitional Probability (TP) computations are regarded as a powerful learning mechanism that is functional early in development and has been proposed as an initial bootstrapping device for speech segmentation. However, a recent study casts doubt on the robustness of early statistical word-learning. Johnson and Tyler (2010) showed that when 8-month-olds are presented with artificial languages where TPs between syllables are reliable cues to word boundaries but that contain words of varying length, infants fail to show word segmentation. Given previous evidence that familiar words facilitate segmentation (Bortfeld, Morgan, Golinkoff, & Rathbun, 2005), we investigated the conditions under which 8-month-old French-learning infants can succeed in segmenting an artificial language. We found that infants can use TPs to segment a language of uniform length words (Experiment 1) and a language of nonuniform length words containing the familiar word "maman" (/mama/, mommy in French; Experiment 2), but not a similar language of nonuniform length words containing the pseudo-word /mama/ (Experiment 3). We interpret these findings as evidence that 8-month-olds can use familiar words and TPs in combination to segment fluent speech, providing initial evidence for 8-month-olds' ability to combine top-down and bottom-up speech segmentation procedures. (Contains 2 tables, 1 figure, and 2 footnotes.)