We collected a corpus of human-human task-oriented dialogs rich in dissatisfaction and built a model that used prosodic features to predict when the user was likely dissatisfied. For utterances this attained a F.25 score of 0.62,against a baseline of
0.39. Based on qualitative observations and failure analysis, we discuss likely ways to improve this result to make it have practical utility.
