  Speech repairs occur often in spontaneous spoken dialogues. The ability to
detect and correct those repairs is necessary for any spoken language system.
We present a framework to detect and correct speech repairs where all relevant
levels of information, i.e., acoustics, lexis, syntax and semantics can be
integrated. The basic idea is to reduce the search space for repairs as soon as
possible by cascading filters that involve more and more features. At first an
acoustic module generates hypotheses about the existence of a repair. Second a
stochastic model suggests a correction for every hypothesis. Well scored
corrections are inserted as new paths in the word lattice. Finally a lattice
parser decides on accepting the rep air.
