Lazlo Ring

Designing relational agents as long term social companions for older adults

Older adults with strong social connections are at a reduced risk for health problems and mortality. We describe two field studies to inform the development of a virtual agent designed to provide long-term, continuous social support to isolated older adults. Findings include the topics that older adults would like to discuss with a companion agent, in addition to overall reactions to interacting with a remote-controlled companion agent installed in their home for a week. Results indicate a generally positive attitude towards companion agents and a rich research agenda for virtual companion agents.

Empathic Touch by Relational Agents

We describe a series of experiments with an agent designed to model human conversational touch-capable of physically touching users in synchrony with speech and other nonverbal communicative behavior-and its use in expressing empathy to users in distress. The agent is composed of an animated human face that is displayed on a monitor affixed to the top of a human mannequin, with touch conveyed by an air bladder that squeezes a users hand. We demonstrate that when touch is used alone, hand squeeze pressure and number of squeezes are associated with user perceptions of affect arousal conveyed by an agent, while number of squeezes and squeeze duration are associated with affect valence. We also show that, when affect-relevant cues are present in facial display, speech prosody, and touch used simultaneously by the agent, facial display dominates user perceptions of affect valence, and facial display and prosody are associated with affect arousal, while touch had little effect. Finally, we show that when touch is used in the context of an empathic, comforting interaction (but without the manipulation of affect cues in other modalities), it can lead to better perceptions of relationship with the agent, but only for users who are comfortable being touched by other people.

Social support agents for older adults: longitudinal affective computing in the home

Loneliness and social isolation are significant problems in older adult populations. We describe the design of a multimodal conversational agent-based system designed to provide longitudinal social support to isolated older adults. Results from a requirements analysis study and a remote “Wizard-of-Oz” study are presented that inform the design of the autonomous social support agent. An exploratory pilot study was conducted in which the agent was placed in the homes of 14 older adults for a week. Results indicate high levels of acceptance and satisfaction of the system. Results also indicate that when the agent proactively draws elders into interactions, triggered by a motion sensor, it is more effective at addressing loneliness than when the agent passively relies upon elders to initiate interactions. We discuss future research opportunities for affective computing to address this important societal problem.

Addressing Loneliness and Isolation in Older Adults: Proactive Affective Agents Provide Better Support

Loneliness and social isolation are significant problems in older adult populations. We describe a conversational agent-based system designed to provide longitudinal social support to isolated older adults. Results from an exploratory pilot study indicate that when the agent proactively draws elders into interactions, it is more effective at addressing loneliness than when the agent passively relies upon elders to initiate interactions. We discuss future research opportunities for affective computing to address this important societal problem.

DynamicDuo: Co-presenting with Virtual Agents

The quality of most professional oral presentations is often poor, owing to a number of factors, including public speaking anxiety. We present DynamicDuo, a system that uses an automated, life-sized, animated agent to help inexperienced speakers deliver their presentations in front of an audience. The design of the system was informed by an analysis of TED talks given by two human presenters to identify the most common dual-presentation formats and transition behaviors used. In a within-subjects study (N=12) comparing co-presenting with DynamicDuo against solo-presenting with conventional presentation software, we demonstrated that our system led to significant improvements in public speaking anxiety and speaking confidence for non-native English speakers. Judges who viewed videotapes of these presentations rated those with DynamicDuo significantly higher on speech quality and overall presentation quality for all presenters.

The Right Agent for the Job

The visual design of virtual agents presents developers with a very large number of choices. We conducted a series of studies using Amazon’s Mechanical Turk that demonstrate that there are no design universals for characters, optimal design of character proportion and rendering style depends on the task domain and user characteristics. Specifically, we found these adjustments to an agent’s appearance directly effected how users rated it based on whether it was discussing social or medical content. The results of this research aim to help create visual guidelines for the development of domain specific virtual agents.

A Robotic Companion for Social Support of Isolated Older Adults

We demonstrate interaction with a relational agent, embodied as a robot, to provide social support for isolated older adults. Our robot supports multiple activities, including discussing the weather, playing cards and checkers socially, maintaining a calendar, talking about family and friends, discussing nutrition, recording life stories, exercise coaching and making video calls.

Making it personal: end-user authoring of health narratives delivered by virtual agents

We describe a design study in which five different tools are compared for end-user authoring of personal stories to be told by an embodied conversational agent. The tools provide varying degrees of control over the agents verbal and nonverbal behavior. Results indicate that users are more satisfied when their stories are delivered by a virtual agent compared to plain text, are more satisfied when provided with tools to control the agents prosody compared to facial display of emotion, and are most satisfied when they have the most control over all aspects of the agents delivery.

Increasing Engagement with Virtual Agents Using Automatic Camera Motion

We describe a series of algorithms which automatically control camera position in a virtual environment while a user is engaged in a simulated face-to-face dialog with a single virtual agent. The common objective of the algorithms is to increase user engagement with the interaction. In our work, we describe three different automated camera control systems that: (1) control the camera’s position based on topic changes in dialog; (2) use sentiment analysis to control the camera-to-agent distance; and (3) adjust the camera’s depth-of-field based on “important” segments of the dialog. Evaluation studies of each method are described. We find that changing camera position based on topic shifts results in significant increases in a self-reported measure of engagement, while the other methods seem to actually decrease user engagement. Interpretations and ramifications of the results are discussed.

Longitudinal affective computing: virtual agents that respond to user mood

We present two empirical studies which examine user mood in long-term interaction with virtual conversational agents. The first study finds evidence for mood as a longitudinal construct independent of momentary affect and demonstrates that mood can be reliably identified by human judges observing user-agent interactions. The second study demonstrates that mood is an important consideration for virtual agents designed to persuade users, by showing that favors are more persuasive than direct requests when users are in negative moods, while direct requests are more persuasive for users in positive moods.