We describe an experimentalWizard-of-Oz-setup for the integration of emotional strategies into spoken dialogue management. With this setup we seek to evaluate different approaches to emotional dialogue strategies in human computer interaction with a spoken dialogue system. The study aims to analyse what kinds of emotional strategies work best in spoken dialogue management especially facing the problem that users may not be honest about their emotions. Therefore as well direct (user is asked about his state) as indirect (measurements of psychophysiological features) evidence is considered for the evaluation of our strategies.

The goal of our research is the development of algorithms for automatic estimation of a person's verbal intelligence based on the analysis of transcribed spoken utterances. In this paper we present the corpus of German native speakers' monologues and dialogues about the same topics collected at the University of Ulm, Germany. The monologues were descriptions of two short films; the dialogues were discussions about problems of German education. The data corpus contains the verbal intelligence quotients of each speaker, which were measured with the Hamburg Wechsler Intelligence Test for Adults. In this paper we describe our corpus, why we decided to create it, and how it was collected. We also describe some approaches which can be applied to the transcribed spoken utterances for extraction of different features which could have a correlation with a person's verbal intelligence. The data corpus consists of 71 monologues and 30 dialogues (about 10 hours of audio data).