We discuss an interactive approach to robust interpretation in a large scale speech-to-speech translation system. Where other interactive approaches to robust interpretation have depended upon domain dependent repair rules, the approach described here operates efficiently without any such hand-coded repair knowledge and yields a 37% reduction in error rate over a corpus of noisy sentences.