- PAR ID:
- 10177559
- Date Published:
- Journal Name:
- International Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1 to 11
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This paper explores avatar identification in creative story- telling applications where users create their own story and environment. We present a study that investigated the effects of avatar facial similarity to the user on the quality of the story product they create. The children told a story using a digital puppet-based storytelling system by inter- acting with a physical puppet box that was augmented with a real-time video feed of the puppet enactment. We used a facial morphing technique to manipulate avatar facial similarity to the user. The resulting morphed image was applied to each participants puppet character, thus creating a custom avatar for each child to use in story creation. We hypothesized that the more familiar avatars appeared to participants, the stronger the sense of character identification would be, resulting in higher story quality. The proposed rationale is that visual familiarity may lead participants to draw richer story details from their past real-life experiences. Qualitative analysis of the stories supported our hypothesis. Our results contribute to avatar design in children's creative storytelling applications.more » « less
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The use of virtual humans (i.e., avatars) holds the potential for interactive, automated interaction in domains such as remote communication, customer service, or public announcements. For signed language users, signing avatars could potentially provide accessible content by sharing information in the signer's preferred or native language. As the development of signing avatars has gained traction in recent years, researchers have come up with many different methods of creating signing avatars. The resulting avatars vary widely in their appearance, the naturalness of their movements, and facial expressions—all of which may potentially impact users' acceptance of the avatars. We designed a study to test the effects of these intrinsic properties of different signing avatars while also examining the extent to which people's own language experiences change their responses to signing avatars. We created video stimuli showing individual signs produced by (1) a live human signer (Human), (2) an avatar made using computer-synthesized animation (CS Avatar), and (3) an avatar made using high-fidelity motion capture (Mocap avatar). We surveyed 191 American Sign Language users, including Deaf ( N = 83), Hard-of-Hearing ( N = 34), and Hearing ( N = 67) groups. Participants rated the three signers on multiple dimensions, which were then combined to form ratings of Attitudes, Impressions, Comprehension, and Naturalness. Analyses demonstrated that the Mocap avatar was rated significantly more positively than the CS avatar on all primary variables. Correlations revealed that signers who acquire sign language later in life are more accepting of and likely to have positive impressions of signing avatars. Finally, those who learned ASL earlier were more likely to give lower, more negative ratings to the CS avatar, but we did not see this association for the Mocap avatar or the Human signer. Together, these findings suggest that movement quality and appearance significantly impact users' ratings of signing avatars and show that signed language users with earlier age of ASL acquisition are the most sensitive to movement quality issues seen in computer-generated avatars. We suggest that future efforts to develop signing avatars consider retaining the fluid movement qualities integral to signed languages.more » « less
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When young children create, they are exploring their emerging skills. And when young children reflect, they are transforming their learning experiences. Yet early childhood play environments often lack toys and tools to scaffold reflection. In this work, we design a stuffed animal robot to converse with young children and prompt creative reflection through open-ended storytelling. We also contribute six design goals for child-robot interaction design. In a hybrid Wizard of Oz study, 33 children ages 4-5 years old across 10 U.S. states engaged in creative play then conversed with a stuffed animal robot to tell a story about their creation. By analyzing children’s story transcripts, we discover four approaches that young children use when responding to the robot’s reflective prompting: Imaginative, Narrative Recall, Process-Oriented, and Descriptive Labeling. Across these approaches, we find that open-ended child-robot interaction can integrate personally meaningful reflective storytelling into diverse creative play practices.more » « less
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We present a novel prompting strategy for artificial intelligence driven digital avatars. To better quantify how our prompting strategy affects anthropomorphic features like humor, authenticity, and favorability we present Crowd Vote - an adaptation of Crowd Score that allows for judges to elect a large language model (LLM) candidate over competitors answering the same or similar prompts. To visualize the responses of our LLM, and the effectiveness of our prompting strategy we propose an end-to-end framework for creating high-fidelity artificial intelligence (AI) driven digital avatars. This pipeline effectively captures an individual's essence for interaction and our streaming algorithm delivers a high-quality digital avatar with real-time audio-video streaming from server to mobile device. Both our visualization tool, and our Crowd Vote metrics demonstrate our AI driven digital avatars have state-of-the-art humor, authenticity, and favorability outperforming all competitors and baselines. In the case of our Donald Trump and Joe Biden avatars, their authenticity and favorability are rated higher than even their real-world equivalents.
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Abstract As the metaverse expands, understanding how people use virtual reality to learn and connect is increasingly important. We used the Transformed Social Interaction paradigm (Bailenson et al., 2004) to examine different avatar identities and environments over time. In Study 1 (n = 81), entitativity, presence, enjoyment, and realism increased over 8 weeks. Avatars that resembled participants increased synchrony, similarities in moment-to-moment nonverbal behaviors between participants. Moreover, self-avatars increased self-presence and realism, but decreased enjoyment, compared to uniform avatars. In Study 2 (n = 137), participants cycled through 192 unique virtual environments. As visible space increased, so did nonverbal synchrony, perceived restorativeness, entitativity, pleasure, arousal, self- and spatial presence, enjoyment, and realism. Outdoor environments increased perceived restorativeness and enjoyment more than indoor environments. Self-presence and realism increased over time in both studies. We discuss implications of avatar appearance and environmental context on social behavior in classroom contexts over time.