Attention and Emotion Based Adaption of Dialog Systems

  • In this work methods are described, which are used for an individual adaption of a dialog system. Anyway, an automatic real-time capable visual user attention estimation for a face to face human machine interaction is described. Furthermore, an emotion estimation is presented, which combines a visual and an acoustic method. Both, the attention estimation and the visual emotion estimation based on Active Appearance Models (AAMs). Certainly, for the attention estimation Multilayer Perceptrons (MLPs) are used to map the Active Appearance Parameters (AAM-Parameters) onto the current head pose. Afterwards, the chronology of the head poses is classified as attention or inattention. In the visual emotion estimation the AAM-Parameter will be classified by a Support-Vector-Machine (SVM). The acoustic emotion estimation also use a SVM to classifies emotion related audio signal features into the 5 basis emotions (neutral, happy, sad, anger, surprise). Afterward, a Bayes network is used to combine the results of the visual and the acoustic estimation in the decision level. The visual attention estimation as well as the emotion estimation will be used in service robotic to allow a more natural and human like dialog. Furthermore, the human head pose is very efficient interpreted as head nodding or shaking by the use of adaptive statistical moments. Especially, the head movement of many demented people are restricted, so they often only use their eyes to look around. For that reason, this work examine a simple gaze estimation with the help of an ordinary webcam. Moreover, a full body user re-identification method is described, which allows an individual state estimation of several people for hight dynamic situations. In this work an appearance based method is described, which allows a fast people re-identification over a short time span to allow the usage of individual parameter.

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Metadaten
Author:Sebastian Hommel, Ahmad Rabie, Uwe Handmann
DOI:https://doi.org/10.1007/978-3-642-33959-2_12
Parent Title (English):Intelligent Systems: Models and Applications
Document Type:Part of a Book
Language:German
Year of Completion:2013
Date of first Publication:2019/02/11
Release Date:2019/02/11
First Page:215
Last Page:235
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):License LogoNo Creative Commons