Spoken language contains disfluencies, which include editing terms such as uh and um as well as repeats and corrections. In less than ten years the question of how disfluencies are handled by the human sentence comprehension system has gone from virtually ignored to a topic of major interest in computational linguistics and psycholinguistics. We discuss relevant empirical findings and describe a computational model that captures how disfluencies influence parsing and comprehension. The research reviewed shows that the parser, which presumably evolved to handle conversations, deals with disfluencies in a way that is efficient and linguistically principled. The success of this research program reinforces the current trend in cognitive science to view cognitive mechanisms as adaptations to real-world constraints and challenges.