language: en

MULTIMEDIA MEETS MACHINE LEARNING

STEFAN M UNCH
Institute for Real-Time Computer Systems & Robotics, University of Karlsruhe,
Kaiserstr. 12, D-76128 Karlsruhe, Germany.

Abstract. The application of Machine Learning techniques to multimedia and multimodal systems, resp., seems to be a promising approach in order to enhance the systems' capabilities. Especially in multimodal systems which support human-computer interaction (HCI) via several input/output channels in parallel, intelligent mechanisms are needed in order to process the user's inputs and to select the best output modality. In this paper, we will deal with a multi-agent system which introduces some kind of haptic feedback to the user interface. The main task of the system is to predict the next user action in order to launch the haptic feedback selectively and to adapt this capability over time to both, the user's behavior and the application's user interface structure. Therefore, a statistical interaction model is generated and managed based on stochastic classification methods.

Key Words. Multimedia, Multimodality, Haptic Output, Man-Machine-Systems, Human-Computer Interaction, Classification, User Modelling

1 INTRODUCTION