Conversational interfaces have been argued to have advantages over traditional GUIs due to having a more human-like interaction. The rise in popularity of conversational agents has enabled humans to interact with machines more naturally. There is a growing familiarity among people with conversational interactions mediated by technology due to the widespread use of mobile devices and messaging services such as WhatsApp, WeChat, and Telegram. Today, over half the population on our planet has access to the Internet with ever-lowering barriers of accessibility. This tutorial will showcase the benefits of employing novel conversational interfaces in the domains of Health and Wellbeing, Information Retrieval, and Crowd Computing. We will discuss the potential of conversational interfaces in facilitating and mediating the interactions of people with AI systems. The tutorial will include an interactive component to provide participants with an opportunity to build conversational interfaces.
Assistant Professor in the Software Technology department
Delft University of Technology, the Netherlands.
Today mental health is a global concern among youth and working professionals. Due to social stigma, lack of awareness, and unavailability and inaccessibility of proper treatment. Artificial intelligence-based digital solutions have provided diagnosis, early detection, and therapy for many mental health illnesses like depression and anxiety in recent years.
This tutorial aims to provide theoretical and hands-on sessions for understanding emotion from text, audio and video using machine learning and deep learning for depression and anxiety detection.
Why you used those words! Understanding emotion and context from text
Speakers: Dr. Ajit Kumar, Dr. Bong Jun (David) Choi
|1||Understanding sentiment and emotion||Dr. Bong Jun (David) Choi||30 minutes|
|2||Detecting depression and finding the topic of discussion||Dr. Ajit Kumar||60 minutes|
Dr. David (Bong Jun) Choi
Professor in School of Computer Science and Engineering & School of Electronic Engineering
Soongsil University, Seoul, Korea
Dr. Ajit Kumar
Postdoctoral Research Fellow
School of Computer Science and Engineering,
Soongsil University, South Korea