17 research outputs found

    Interactive narration with a child: impact of prosody and facial expressions

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    International audienceIntelligent Virtual Agents are suitable means for interactive sto-rytelling for children. The engagement level of child interaction with virtual agents is a challenging issue in this area. However, the characteristics of child-agent interaction received moderate to little attention in scientific studies whereas such knowledge may be crucial to design specific applications. This article proposes a Wizard of Oz platform for interactive narration. An experimental study in the context of interactive story-telling exploiting this platform is presented to evaluate the impact of agent prosody and facial expressions on child participation during storytelling. The results show that the use of the virtual agent with prosody and facial expression modalities improves the engagement of children in interaction during the narrative sessions

    Robot-Mediated Interviews: a Robotic Intermediary for Facilitating Communication with Children

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    Robots have been used in a variety of education, therapy or entertainment contexts. This thesis introduces the novel application of using humanoid robots for Robot-Mediated Interviews (RMIs). In the initial stages of this research it was necessary to first establish as a baseline if children would respond to a robot in an interview setting, therefore the first study compared how children responded to a robot and a human in an interview setting. Following this successful initial investigation, the second study expanded on this research by examining how children would respond to different types and difficulty of questions from a robot compared to a human interviewer. Building on these studies, the third study investigated how a RMI approach would work for children with special needs. Following the positive results from the three studies indicating that a RMI approach may have some potential, three separate user panel sessions were organised with user groups that have expertise in working with children and for whom the system would be potentially useful in their daily work. The panel sessions were designed to gather feedback on the previous studies and outline a set of requirements to make a RMI system feasible for real world users. The feedback and requirements from the user groups were considered and implemented in the system before conducting a final field trial of the system with a potential real world user. The results of the studies in this research reveal that the children generally interacted with KASPAR in a very similar to how they interacted with a human interviewer regardless of question type or difficulty. The feedback gathered from experts working with children suggested that the three most important and desirable features of a RMI system were: reliability, flexibility and ease of use. The feedback from the experts also indicated that a RMI system would most likely be used with children with special needs. The final field trial with 10 children and a potential real world user illustrated that a RMI system could potentially be used effectively outside of a research context, with all of the children in the trial responding to the robot. Feedback from the educational psychologist testing the system would suggest that a RMI approach could have real world implications if the system were developed further

    Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories

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    In 1970, Masahiro Mori proposed the uncanny valley (UV), a region in a human-likeness continuum where an entity risks eliciting a cold, eerie, repellent feeling. Recent studies have shown that this feeling can be elicited by entities modeled not only on humans but also nonhuman animals. The perceptual and cognitive mechanisms underlying the UV effect are not well understood, although many theories have been proposed to explain them. To test the predictions of nine classes of theories, a within-subjects experiment was conducted with 136 participants. The theories’ predictions were compared with ratings of 10 classes of stimuli on eeriness and coldness indices. One type of theory, configural processing, predicted eight out of nine significant effects. Atypicality, in its extended form, in which the uncanny valley effect is amplified by the stimulus appearing more human, also predicted eight. Threat avoidance predicted seven; atypicality, perceptual mismatch, and mismatch+ predicted six; category+, novelty avoidance, mate selection, and psychopathy avoidance predicted five; and category uncertainty predicted three. Empathy's main prediction was not supported. Given that the number of significant effects predicted depends partly on our choice of hypotheses, a detailed consideration of each result is advised. We do, however, note the methodological value of examining many competing theories in the same experiment

    Speech Synthesis for the Generation of Artificial Personality

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    ACII 2009: Affective Computing and Intelligent Interaction. Proceedings of the Doctoral Consortium 2009

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    Affective Brain-Computer Interfaces

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    ALIUS Bulletin n°2

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