“For Heaven’s Sake, Gimme a Live Person!” Designing Emotion-Detection Customer Care Voice Applications in Automated Call Centers

With increasing complexity of automated telephone-based applications, we require new means to detect problems occurring in the dialog between system and user in order to support task completion. Anger and frustration are important symptoms indicating that task completion and user satisfaction may be endangered. This chapter describes extensively a variety of aspects that are relevant for performing anger detection in interactive voice response (IVR) systems and describes an anger detection system that takes into account several knowledge sources to robustly detect angry user turns. We consider acoustic, linguistic, and interaction parameter-based information that can be collected and exploited for anger detection. Further, we introduce a subcomponent that is able to estimate the emotional state of the caller based on the caller’s previous emotional state. Based on a corpus of 1,911 calls from an IVR system, we demonstrate the various aspects of angry and frustrated callers.