Self-corrections or repairs are often left unmodeled in current spoken language systems although they occur in about 10% of spontaneous utterances. We report on a study of acoustic-prosodic repair cues of potential use for repair identification, word fragment identification, and repair correction. The relative contributions of these and other text-based cues to repair identification were tested in a statistical model that achieved a precision rate of 91 % and recall of 86%.