The Dialogue Problem Detector (DPD) is part of the User Model component, and its task is to predict the presence of an ASR error in the user's utterance. It uses seven parameters to train a Naive Bayes classifier.

The precision and recall measures of the class "error" on the test data are 92% and 53%, respectively, and the figures suggest that the DPD might be a useful component, reducing the number of system's misunderstandings and user's errors during the dialogue.

More information on the DUMAS project can be found at:
http://www.sics.se/dumas/