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A major problem of understanding language in spoken dialog systems is to detect recognition errors in the output of a speech recognizer. Such a capability is the basis of implementing repair strategies that allow a dialog system to handle communication about misunderstandings similarly to other clarifications. In this paper we present a two-phase approach that combines chunk and dependency parsing and takes the global syntactic structure of recognizer output into account. This enables us to identify dependencies between chunks and detect syntactical errors caused by word confusions in case dependency constraints are violated. Finally, we apply these diagnostics to dialog modeling and discuss how the resulting error information can be used by clarification strategies.
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