Robots that express emotion elicit better human teaching

Leyzberg, Dan; Avrunin, Eleanor; Liu, Jenny; Scassellati, Brian

doi:10.1145/1957656.1957789

Cited by 36 publications

(23 citation statements)

References 17 publications

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“…For example, Niculescu et al found that varying the pitch of a robot's voice had a strong influence on the way users rated the overall interaction quality, and encouraged further research on the topic [34]. Expressing emotions in the voice might also be beneficial in some human-robot interactions: Leyzberg et al [25] and Tielman et al [48] found that people tended to co-operate more with robots that expressed themselves using appropriate emotional verbal feedback.…”

Section: Related Workmentioning

confidence: 99%

Can you Tell the Robot by the Voice? An Exploratory Study on the Role of Voice in the Perception of Robots

McGinn

Torre

2019

2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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It is well established that a robot's visual appearance plays a significant role in how it is perceived. Considerable time and resources are usually dedicated to help ensure that the visual aesthetics of social robots are pleasing to users and helps facilitate clear communication. However, relatively little consideration is given to how the voice of the robot should sound, which may have adverse effects on acceptance and clarity of communication. In this study, we explore the mental images people form when they hear robots speaking. In our experiment, participants listened to several voices, and for each voice they were asked to choose a robot, from a selection of eight commonly used social robot platforms, that was best suited to have that voice. The voices were manipulated in terms of naturalness, gender, and accent. Results showed that a) participants seldom matched robots with the voices that were used in previous HRI studies, b) the gender and naturalness vocal manipulations strongly affected participants' selection, and c) the linguistic content of the utterances spoken by the voices does not affect people's selection. This finding suggests that people associate voices with robot pictures, even when the content of spoken utterances was unintelligible. Our findings indicate that both a robot's voice and its appearance contribute to robot perception. Thus, giving a mismatched voice to a robot might introduce a confounding effect in HRI studies. We therefore suggest that voice design should be considered more thoroughly when planning spoken human-robot interactions.

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Section: Related Workmentioning

confidence: 99%

Can you Tell the Robot by the Voice? An Exploratory Study on the Role of Voice in the Perception of Robots

McGinn

Torre

2019

2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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“…We chose Keepon because it is particularly well suited to expressive non-threatening social communication [13,14].…”

Section: Robotmentioning

confidence: 99%

Personalizing robot tutors to individuals' learning differences

Leyzberg

Spaulding

Scassellati

2014

Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction

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186

142

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In education research, there is a widely-cited result called "Bloom's two sigma" that characterizes the differences in learning outcomes between students who receive one-on-one tutoring and those who receive traditional classroom instruction [1]. Tutored students scored in the 95 th percentile, or two sigmas above the mean, on average, compared to students who received traditional classroom instruction. In human-robot interaction research, however, there is relatively little work exploring the potential benefits of personalizing a robot's actions to an individual's strengths and weaknesses. In this study, participants solved grid-based logic puzzles with the help of a personalized or non-personalized robot tutor. Participants' puzzle solving times were compared between two non-personalized control conditions and two personalized conditions (n=80). Although the robot's personalizations were less sophisticated than what a human tutor can do, we still witnessed a "one-sigma" improvement (68 th percentile) in post-tests between treatment and control groups. We present these results as evidence that even relatively simple personalizations can yield significant benefits in educational or assistive human-robot interactions.

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“…Leyzberg et al (2011) showed that robots that express emotions elicited better human teaching. A long-term experiment conducted by Bickmore and Picard (2005) showed that an agent with relational behavior, including social-emotional responses, contributed to increasing participants' positive attitude about exercise.…”

Section: Introductionmentioning

confidence: 99%

Emotional Expression in Simple Line Drawings of a Robot's Face Leads to Higher Offers in the Ultimatum Game

Terada

Takeuchi

2017

Front. Psychol.

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In the present study, we investigated whether expressing emotional states using a simple line drawing to represent a robot's face can serve to elicit altruistic behavior from humans. An experimental investigation was conducted in which human participants interacted with a humanoid robot whose facial expression was shown on an LCD monitor that was mounted as its head (Study 1). Participants were asked to play the ultimatum game, which is usually used to measure human altruistic behavior. All participants were assigned to be the proposer and were instructed to decide their offer within 1 min by controlling a slider bar. The corners of the robot's mouth, as indicated by the line drawing, simply moved upward, or downward depending on the position of the slider bar. The results suggest that the change in the facial expression depicted by a simple line drawing of a face significantly affected the participant's final offer in the ultimatum game. The offers were increased by 13% when subjects were shown contingent changes of facial expression. The results were compared with an experiment in a teleoperation setting in which participants interacted with another person through a computer display showing the same line drawings used in Study 1 (Study 2). The results showed that offers were 15% higher if participants were shown a contingent facial expression change. Together, Studies 1 and 2 indicate that emotional expression in simple line drawings of a robot's face elicits the same higher offer from humans as a human telepresence does.

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Robots that express emotion elicit better human teaching

Cited by 36 publications

References 17 publications

Can you Tell the Robot by the Voice? An Exploratory Study on the Role of Voice in the Perception of Robots

Can you Tell the Robot by the Voice? An Exploratory Study on the Role of Voice in the Perception of Robots

Personalizing robot tutors to individuals' learning differences

Emotional Expression in Simple Line Drawings of a Robot's Face Leads to Higher Offers in the Ultimatum Game

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