Intelligent Interaction is a multidisciplinary topic in which computer science meets social science to investigate, design and evaluate novel forms of multimodal human-computer interaction.
Research in Intelligent Interaction concerns the perception-action cycle of understanding human behaviours and generating system responses, supporting an ongoing dialogue with the user. Understanding the user –by automated evaluation of speech, pose, gestures, touch, facial expressions, social behaviours, interactions with other humans, bio-physical signals and all content humans create– should inform the generation of intuitive and satisfying system responses. By understanding how and why people use interactive media, interactive systems can be made more socially capable, safe, acceptable and fun. Evaluation of the resulting systems generally focuses on the perception that the user has of them and the experience that they engender. These issues are investigated through the design, implementation, and analysis of systems across different application areas and across a variety of contexts.
Example application areas include social robots; tangible and tactile interaction; conversations with intelligent agents; mobile coaches and multimodal training games and more.
The available Track 1 topics in this edition of the conference are the following:
Machine learning models to support teleoperated robotics
Spoken Conversational Interaction (SCI) with a robot
Aging in place
"Exposing the brain of a robot"
Analysing anthropomorphism and animacy in tweets
Analysis of user interactions with a VR art exhibition
Preferred error mitigation strategies in a hospital across different contexts
Clarifying questions for vague conditions in product search
The design and development of a real-time feedback system for running using XSens DOT technology
The design and development of a real-time feedback system for running using the OpenPose computer vision library
Performance comparison of XSens DOT and OpenPose in estimating joint angles in sports and movement
Analysing linguistic alignment in online conversations
Trustworthiness modelling (of data for ML)
Computational creativity / language generation
More details are available on Canvas.
For further information on the content of this track, you may contact the track chair: Mariët Theune