How People Talk with Robots: Designing Dialog to Reduce User Uncertainty (original) (raw)
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A dialog system for comparative user studies on robot verbal behavior
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In domestic social robot systems the dialog system is often the main user interface. The verbal behavior of such a robot, therefore, plays crucial role in human-robot interaction. Comparative user studies on various verbal behaviors of a robot can effectively contribute to human-robot interaction research. In this paper we present a dialog system that can be easily configured to demonstrate different verbal, initiativetaking behaviors for a robot and, thus, can be used as a platform for such comparative user studies. The pilot study we conducted does not only provide strong evidence for this suitability, but also reveals benefits of comparative studies on a real robot in general.
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This paper reports the preliminary results of a human- robot dialogue analysis in the real world with the goal of understanding users’ interaction patterns. We analyzed the dialogue log data of Roboceptionist, a robotic receptionist located in a high-traffic area in an academic building [2][3]. The results show that (i) the occupation and background (persona) of the robot help people establish common ground with the robot, and (ii) there is great variability in the extent that users follow social norms of human-human dialogues in human-robot dialogues. Based on these results, we describe implications for designing the dialogue of a social robot.
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Abstract The development of robots that are able to accept instructions, via a friendly interface, in terms of concepts that are familiar to a human user remains a challenge. It is argued that designing and building such intelligent robots can be seen as the problem of integrating four main dimensions: human-robot communication, sensory motor skills and perception, decision-making capabilities, and learning.
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Industry, military, and academia are showing increasing interest in collaborative human-robot teaming in a variety of task contexts. Designing effective user interfaces for human-robot interaction is an ongoing challenge, and a variety of single-and multiple-modality interfaces have been explored. Our work is to develop a bi-directional natural language interface for remote human-robot collaboration in physically situated tasks. When combined with a visual interface and audio cueing, we intend for the natural language interface to provide a naturalistic user experience that requires little training. Building the language portion of this interface requires first understanding how potential users would speak to the robot. In this paper, we describe our elicitation of minimally-constrained robot-directed language, observations about the users' language behavior, and future directions for constructing an automated robotic system that can accommodate these language needs.
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Communication with artificial interaction partners differs in many ways from communication among humans, and often so in the very first utterance. That is, in human-computer and human-robot interaction users address their artificial communication partner on the basis of preconceptions. The current paper addresses the nature of speakers’ preconceptions about robots and computers and the role these preconceptions play in human-computer and human-robot interactions. That is, I will show that a) two types of preconceptions as opposing poles of the same dimension of interpersonal relationship can be distinguished, b) these types can be readily identified on the basis of surface cues in the users’ utterances, b) these preconceptions correlate with the users’ linguistic choices on all linguistic levels, and d) these preconceptions also influence the speakers’ interactional behaviour, in particular, with respect to which their linguistic behaviour can be influenced, that is, in how far spea...
Welcoming Our Robot Overlords: Initial Expectations About Interaction With a Robot
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ABSTRACT Because robots and other electronic agents perform increasingly social functions, people will soon face the possibility of more frequent human–robot interactions. But what kinds of expectations do people bring with them into these potential interactions? Based on the possibility of a human-to-human interaction script, the current research hypothesized that people will be more uncertain about, anticipate less social attraction to, and expect less social presence when they expect to interact with a robot as opposed to another human. An experiment was designed in which people were told they would interact with either a robot or another person, and each of these three expectations was measured. The data were consistent with each of three hypotheses. These findings are discussed, as are avenues for future research.
Initial Interaction Expectations with Robots: Testing the Human-To-Human Interaction Script
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As social robotics becomes more utilized and routine in everyday situations, individuals will be interacting with social robots in a variety of contexts. Centered on the use of human-to-human interaction scripts, the current study hypothesized that individuals would be more uncertain, have less liking and anticipate less social presence when they are told that they will be interacting with a social robot as opposed to another person. Additionally, the current study utilized a two-time measurement model experiment to explore perceptions of interacting with either a robot or human. Data were consistent with hypotheses. Research questions examined perceptions from Time 1 to Time 2 for the robot condition on the dependent variables. Findings are discussed in light of future research studies.
User Experience in Human-Robot Interactions
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This paper describes our experiments concerning human-robot interaction and its evaluation in order to measure the user's communication experience with the robot. We assume that the user's evaluation of the interaction reflects their participation in the interaction as a participant, and correlates with their own multimodal signaling as well as with their perception of the robot's communicative capability. The work contributes to evaluation methodology of intelligent situated agents, as we explore the role and effect of the user's own activity in successful communication experience, and ultimately in their evaluation of interactive systems, instead of focusing solely on task completion. This also adds to our understanding of how the interlocutors perceive interaction, and of the important cognitive processes that underlie communication experience in general.
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Modeling interaction with robots raises new and different challenges for dialog modeling than traditional dialog modeling with less embodied machines. We present four case studies of implementing a typical humanrobot interaction scenario with different state ...