Thomas Portele

Emotion Analysis and Emotion-Handling Subdialogues

The chapter presents the cognitive model-based approach of abductive interpretation of emotions that is used in the multimodal dialogue system SmartKom. The approach is based on Ortony, Clore and Collins’ (OCC) model of emotions, which explains emotions by matches or mismatches of the attitudes of an agent with the state of affairs in the relevant situation. We explain how eliciting conditions, i.e., abstract schemata for the explanation of emotions, can be instantiated with general or abstract concepts for attitudes and actions, and further enhanced with conditions and operators for generating reactions, which allow for abductive inference of explanations of emotional states and determination of reactions. During this process concepts that are initially abstract are made concrete. Emotions may work as a self-contained dialogue move. They show a complex relation to explicit communication. Additionally, we present our approach of evaluating indicators of emotions and user states that come from different sources.

SmartKom-Home: The Interface to Home Entertainment

SmartKom-Home demonstrates the use and benefit of an intelligent multimodal interface when controlling entertainment devices like a TV, a recorder, and a jukebox, and when accessing entertainment services like an electronic program guide combining speech and a handheld display with touch input. One important point is emphasizing the functional aspect, i.e., the user’s needs, conveyed to the system in a natural way by speech and gesture, are satisfied. The user does not need to know device-specific features or service idiosyncrasies. The function modeling component in SmartKom-Home has the necessary knowledge to transform the abstract user request into device commands and service queries.

Cognitive-Model-Based Interpretation of Emotions in a Multi-modal Dialog System

The paper presents the cognitive-model-based approach of abductive interpretation of emotions that it is used in the multi-modal dialog system SmartKom. The approach is based on the OCC model of emotions, that explains emotions by matches or mismatches of the attitudes of an agent with the state of affairs in the relevant situation. It is explained how eliciting conditions, i.e. abstract schemata for the explanation of emotions, can be instantiated with general or abstract concepts for attitudes and actions, and further enhanced with conditions and operators for generating reactions, which allow for abductive inference of explanations of emotional states and determination of reactions. During this process concepts that are initially abstract 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.

Data-driven classification of linguistic styles in spoken dialogues

Language users have individual linguistic styles. A spoken dialogue system may benefit from adapting to the linguistic style of a user in input analysis and output generation. To investigate the possibility to automatically classify speakers according to their linguistic style three corpora of spoken dialogues were analyzed. Several numerical parameters were computed for every speaker. These parameters were reduced to linguistically interpretable components by means of a principal component analysis. Classes were established from these components by cluster analysis. Unseen input was classified by trained neural networks with varying error rates depending on corpus type. A first investigation in using special language models for speaker classes was carried out.

Application-Independent Knowledge-Processing in a Task-Oriented Speech-Dialog-System (Applikationsunabhängige Wissensverarbeitung in aufgabenorientierten Sprach-Dialogsystemen)

Summary Spoken language dialog systems allow users to control applications by voice. These systems tightly integrate the applications to control them, even though knowledge sources of the building blocks are often configurable. Some dialog systems controlling multiple applications loosen the coupling. This article introduces a dialog system accessing multiple applications with a dynamic setup that can be changed at run-time, separating the applications from the system. This is achieved by application-independent knowledge processing inside the dialog system based on modular ontological descriptions. A clear interface between dialog system and applications is provided, generic dialog functionality is realized on top of the application independent knowledge processing. Examples illustrate interactions with the system.