14,780 research outputs found
A Virtual Conversational Agent for Teens with Autism: Experimental Results and Design Lessons
We present the design of an online social skills development interface for
teenagers with autism spectrum disorder (ASD). The interface is intended to
enable private conversation practice anywhere, anytime using a web-browser.
Users converse informally with a virtual agent, receiving feedback on nonverbal
cues in real-time, and summary feedback. The prototype was developed in
consultation with an expert UX designer, two psychologists, and a pediatrician.
Using the data from 47 individuals, feedback and dialogue generation were
automated using a hidden Markov model and a schema-driven dialogue manager
capable of handling multi-topic conversations. We conducted a study with nine
high-functioning ASD teenagers. Through a thematic analysis of post-experiment
interviews, identified several key design considerations, notably: 1) Users
should be fully briefed at the outset about the purpose and limitations of the
system, to avoid unrealistic expectations. 2) An interface should incorporate
positive acknowledgment of behavior change. 3) Realistic appearance of a
virtual agent and responsiveness are important in engaging users. 4)
Conversation personalization, for instance in prompting laconic users for more
input and reciprocal questions, would help the teenagers engage for longer
terms and increase the system's utility
Designing friends
Embodied Conversational Agents are virtual humans that can interact with humans using verbal and non-verbal forms of communication. In most cases, they have been designed for short interactions. This paper asks the question how one would start to design synthetic characters that can become your friends. We look at insights from social psychology and propose a methodology for designing friends
Detecting Low Rapport During Natural Interactions in Small Groups from Non-Verbal Behaviour
Rapport, the close and harmonious relationship in which interaction partners
are "in sync" with each other, was shown to result in smoother social
interactions, improved collaboration, and improved interpersonal outcomes. In
this work, we are first to investigate automatic prediction of low rapport
during natural interactions within small groups. This task is challenging given
that rapport only manifests in subtle non-verbal signals that are, in addition,
subject to influences of group dynamics as well as inter-personal
idiosyncrasies. We record videos of unscripted discussions of three to four
people using a multi-view camera system and microphones. We analyse a rich set
of non-verbal signals for rapport detection, namely facial expressions, hand
motion, gaze, speaker turns, and speech prosody. Using facial features, we can
detect low rapport with an average precision of 0.7 (chance level at 0.25),
while incorporating prior knowledge of participants' personalities can even
achieve early prediction without a drop in performance. We further provide a
detailed analysis of different feature sets and the amount of information
contained in different temporal segments of the interactions.Comment: 12 pages, 6 figure
Rules for Responsive Robots: Using Human Interactions to Build Virtual Interactions
Computers seem to be everywhere and to be able to do almost anything. Automobiles have Global Positioning Systems to give advice about travel routes and destinations. Virtual classrooms supplement and sometimes replace face-to-face classroom experiences with web-based systems (such as Blackboard) that allow postings, virtual discussion sections with virtual whiteboards, as well as continuous access to course documents, outlines, and the like. Various forms of âbotsâ search for information about intestinal diseases, plan airline reservations to Tucson, and inform us of the release of new movies that might fit our cinematic preferences. Instead of talking to the agent at AAA, the professor, the librarian, the travel agent, or the cinema-file two doors down, we are interacting with electronic social agents. Some entrepreneurs are even trying to create toys that are sufficiently responsive to engender emotional attachments between the toy and its owner
Guide to the Networked Minds Social Presence Inventory v. 1.2
This document introduces the Networked\ud
Minds Social Presence Inventory. The\ud
inventory is a self-report measure of social\ud
presence, which is commonly defined as the\ud
sense of being together with another in a\ud
mediated environment. The guidelines\ud
provide background on the use of the social\ud
presence scales in studies of usersâ social\ud
communication and interaction with other\ud
humans or with artificially intelligent agents\ud
in virtual environments
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