HCI research has for long been dedicated to better and more naturally facilitating information transfer between humans and machines. Unfortunately, humans' most natural form of communication, speech, is also one of the most difficult modalities to be understood by machines – despite, and perhaps, because it is the highest-bandwidth communication channel we possess. While significant research efforts, from engineering, to linguistic, and to cognitive sciences, have been spent on improving machines' ability to understand speech, the IUI community (and the HCI field at large) has been relatively timid in embracing this modality as a central focus of research. This can be attributed in part to the relatively discouraging levels of accuracy in understanding speech, in contrast with often unfounded claims of success from industry, but also to the intrinsic difficulty of designing and especially evaluating speech and natural language interfaces. As such, the development of interactive speech-based systems is mostly driven by engineering efforts to improve such systems with respect to largely arbitrary performance metrics. Such developments have often been void of any user-centered design principles or consideration for usability or usefulness.
The goal of this course is to inform the IUI community of the current state of speech and natural language research, to dispel some of the myths surrounding speech-based interaction, as well as to provide an opportunity for researchers and practitioners to learn more about how speech recognition and speech synthesis work, what are their limitations, and how they could be used to enhance current interaction paradigms. Through this, we hope that HCI researchers and practitioners will learn how to combine recent advances in speech processing with user-centred principles in designing more usable and useful speech-based interactive systems.
Digital behaviour intervention is a growing area of research which investigates how interactive systems can encourage and support people to change their behaviour, for their own or communal benefits. Personalization plays an important role in this, as the most effective persuasive and motivational strategies are likely to depend on user characteristics such as the user’s personality, affective state, existing attitudes, behaviours, knowledge, and goals. Example application areas include healthcare (e.g., encouraging people to eat more healthily and exercise more), education (e.g., motivating learners to study more), environment (e.g., encouraging people to use less energy and more public transport), and collaborative content development (e.g., incentivising people to annotate resources, participate online). This tutorial will cover the role of personalization in behaviour change technology, and methods and techniques to design personalized behaviour change technology. The tutorial will include both traditional and more recent approaches (such as gamification). It will be highly interactive, with short interactive lectures, and group-based exercises.
User Sentiment and Affect are expected to play a major role that will likely make `that difference’ in future intelligent User Interfaces. In this light, this tutorial aims to give a good introduction into the fields of user Sentiment Analysis and user Affect Modeling, shows the general technology, its current reliability, ways for integration in a user interface context, and latest trends alongside future directions in and for this exciting and potentially game-changing field. In particular, it will feature an interactive `hands-on’ experience of a range of toolkits to enable participants to immediately experience the technology and craft their own solutions.