In this paper we present a system which automatically corrects disfluencies such as repairs and restarts typically occurring in spontaneously spoken speech. The system is based on a noisy-channel model and its development requires no linguistic knowledge, but only annotated texts. Therefore, it has large potential for rapid deployment and the adaptation to new target languages. The experiments were conducted on spontaneously spoken dialogs from the English VERBMOBIL corpus where a recall of 77.2% and a precision of 90.2% was obtained. To demonstrate the feasibility of rapid adaptation additional experiments on the spontaneous Mandarin Chinese CallHome corpus were performed achieving 49.4% recall and 76.8% precision.