In this paper, we present an Embodied Conversational Agent (ECA) enriched with automatic image understanding, using vision data derived from state-of-the-art machine learning techniques for the advancement of autonomous interaction with the elderly or infirm. The agent is developed to conduct health and emotion well-being monitoring for the elderly. It is not only able to conduct question-answering via speech-based interaction, but also able to provide analysis of the user’s surroundings, company, emotional states, hazards and fall actions via visual data using deep learning techniques. The agent is accessible from a web browser and can be communicated with via voice means, with a webcam required for the visual analysis functionality. The system has been evaluated with diverse real-life images to prove its efficiency.
|Title of host publication||Intelligent Virtual Agents|
|Place of Publication||London|
|Publication status||Published - 23 Nov 2016|
|Name||Lecture Notes in Computer Science|