Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance ( Litman et al. , 1999 ) .
automatic detection of poor speech recognition at the dialogue level
D J Litman M A Walker M J Kearns
The research reported here is the first that we know of to automatically analyze a corpus of logs from a spoken dialogue system for the purpose of learning to predict problematic situations . Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance ( Litman et al. , 1999 ) . However , that work was based on a much smaller set of experimental dialogues where the notion of a good or bad dialogue was automatically approximated rather than being labelled by humans .
Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance ( @@CITATION ) .