E-motional advantage: performance and satisfaction gains with affective computing.
ABSTRACT Emotions are now recognized as complex human control systems, crucial to decision making, creativity, playing and learning. Affective technologies may offer improved interaction and commercial promise. In the past, research has focused on technical development work, leaving many questions about user preferences unanswered. For this user-centered study, 60 participants played a simple 'word ladder' game under different controlled conditions. Using 2 x 2 factorial design, and a Wizard of Oz scenario, half the participants interacted with a system that adapted on the basis of the user's emotional expression and half were told the system could react to their emotional expressions. We established that when using an apparently affective system, users perform significantly better and report themselves as feeling significantly happier. We also discuss behavioral responses to the different conditions. These results are relevant to the design of future affective systems.
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ABSTRACT: Affective technologies have potential to enhance human-computer interaction (HCI). The problem is that much development is technically, rather than user driven, raising many unanswered questions about user preferences and opening new areas for research. People naturally incorporate emotional messages during interpersonal communication with other people, but their use of holistic communication including emotional displays during HCI has not been widely reported. Using Wizard-of-Oz (WOZ) methods, experimental design and methods of sequential analysis from the social sciences, we have recorded, analyzed and compared emotional displays of participants during interaction with an apparently affective system and a standard, non-affective version. During interaction, participants portray extremely varied, sometimes intense, ever-changing displays of emotions and these are rated as significantly more positive in the affective computer condition and as significantly more intense in the told affective condition. We also discuss behavioural responses to the different conditions. These results are relevant to the design of future affective systems.Affective Computing and Intelligent Interaction, First International Conference, ACII 2005, Beijing, China, October 22-24, 2005, Proceedings; 01/2005
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ABSTRACT: Automatic detection of the level of human interest is of high relevance for many technical applications, such as automatic customer care or tutoring systems. However, the recognition of spontaneous interest in natural conversations independently of the subject remains a challenge. Identification of human affective states relying on single modalities only is often impossible, even for humans, since different modalities contain partially disjunctive cues. Multimodal approaches to human affect recognition generally are shown to boost recognition performance, yet are evaluated in restrictive laboratory settings only. Herein we introduce a fully automatic processing combination of Active–Appearance–Model-based facial expression, vision-based eye-activity estimation, acoustic features, linguistic analysis, non-linguistic vocalisations, and temporal context information in an early feature fusion process. We provide detailed subject-independent results for classification and regression of the Level of Interest using Support-Vector Machines on an audiovisual interest corpus (AVIC) consisting of spontaneous, conversational speech demonstrating “theoretical” effectiveness of the approach. Further, to evaluate the approach with regards to real-life usability a user-study is conducted for proof of “practical” effectiveness.Image and Vision Computing. 01/2009;
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ABSTRACT: Reading fiction is many people's favorite pastime. There is no denying that one of the needs of human beings is to share what they read and understand other readers' feelings about the books they have read. Recent developments in Web 2.0 technologies characterizing personalized information organization have led to an interest in social tagging behavior of a variety of items, such as books, images, web pages, videos, etc. However, a major issue with this kind of application is that tags are growing in an uncontrolled manner. In fact, it is chaos. Several studies have recognized the existence of affective tags, but there is no user interface designed to separate affective tags from other tags. To address that affective tags are navigation aids for readers, this work gives an account of design of a novel interface for visualization of affective tags at a social cataloging website, LibraryThing.com.Proceedings of the 27th International Conference on Human Factors in Computing Systems, CHI 2009, Extended Abstracts Volume, Boston, MA, USA, April 4-9, 2009; 01/2009