Titlebook: Affective Dialogue Systems; Tutorial and Researc Elisabeth André,Laila Dybkj?r,Paul Heisterkamp Conference proceedings 2004 Springer-Verlag

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Cognitive-Model-Based Interpretation of Emotions in a Multi-modal Dialog Systemt are made concrete. Emotions may work as a self-contained dialog move. They show a complex relation to explicit communication. Additionally we present our approach of analyzing indicators of emotions and user state, that come from different sources.

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STUDIO: A Solution on Adaptive Testing,putes the resulting emotions and their intensities. Emotions are used to inform the selection of pre-scripted scenes and dialog strategies, and their surface realization. The approach has been integrated in two fully operable systems, the CrossTalk II installation and the NECA eShowroom.

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Alexander Proelss,Robert C. Steenkampcripts). We consider that “affective” semantic components in text meaning are recognized by d-scripts and cause their activation, thus simulating speech influence. On the other side, d-scripts define “affective” semantic shifts in texts, which are produced in an emotional state or aimed to affect the listener.

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Neural Architecture for Temporal Emotion Classification ARTMAP neural network was trained by incremental learning to classify the feature vectors resulting from the motion processing stage. Single category nodes corresponding to the expected feature representation code the respective emotion classes. The architecture was tested on the Cohn-Kanade facial expression database.

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0302-9743 emotional state and may attempt to respond to it accordingly. When instead one of the interlocutors is a computer a number of questions arise, such as the following: To what extent are dialogue systems able to simulate such behaviors? Can we learn the mechanisms of emotional be- viors from observin

triptans

https://doi.org/10.1007/978-3-8350-9675-2e to model and classify them reliably. We exemplify these difficulties on the basis of SympaFly, a database with dialogues between users and a fully automatic speech dialogue telephone system for flight reservation and booking, and discuss possible remedies.

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https://doi.org/10.1007/978-3-8350-9675-2he segments were inverse filtered and parametrized using NAQ. Statistical analyses showed significant differences between most studied emotions. Results also showed clear gender differences. Inverse filtering together with NAQ was shown to be a suitable method for analysis of emotional content in continuous speech.