Multimodal Expression of Artificial Emotion in Social Robots Using Color, Motion and Sound

Löffler, Diana; Schmidt, Nina; Tscharn, Robert

doi:10.1145/3171221.3171261

Cited by 85 publications

(63 citation statements)

References 34 publications

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“…A few recent studies have also investigated the design of non-linguistic sounds in HRI [30,27,10]. However, the amount of information that can be communicated by the nonlinguistic utterances is substantially limited, and according to Crumpton and Bethel, "there has been little research into how manipulating a robots voice would affect its users" [11].…”

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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“…More research is needed to assess how other types of behavioral feedback impact the training interaction and how to correctly implement that demeanor into current machine learning techniques. Notwithstanding, research with non-humanoid robots that communicate with nonverbal cues like light [55,56], sound [57,58] or both [37,59,60] is an ongoing area of study in the field of Social Robotics. The next step of this research aims to identify and design light cues and audio utterances that can improve the experience of training robots.…”

Section: Discussionmentioning

confidence: 99%

“…Geometrically shaped robots like the artificial assistant Jibo [34], the robot playmate Cozmo [35], or Mira [36], a robot designed with Pixar's animation style, were developed to use fluid movements and animations to give an organic and emotional impression to the user. Movement, sound, and color are the main outputs used to express emotional feedback in these types of robots [37].…”

Section: Emotional Robotsmentioning

confidence: 99%

Design and Evaluation of a Spherical Robot with Emotion-Like Feedback during Human-Robot Training

Onchi

Lee

2020

Transactions of Japan Society of Kansei Engineering

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While robotic assistants capable of automating many a task are becoming more ubiquitous, the complexity and unfamiliarity of such machines may discourage users from interacting and personalizing their robots. For that reason, the goal of this research is to study how a robot that expresses emotion-like feedback using movement affects the training interaction experience of non-expert users.To that end, a single-eyed spherical robot was developed using a Kansei design approach. A within-subjects experiment, between the robot expressing feedback and a control version that did not, was conducted with participants who had little to no experience interacting with robots. The results showed an increase in arousal when the robot expressed feedback and the overall interaction was considered engaging. Also, a positive correlation between bonding scores and relevance of the task was found. The contributions of this research are toward the development of human-trainable robots with transparent learning behavior.

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“…They found that people could identify the correct emotions corresponding to each role (correctness determined by a pretest without the robot) and the drone's intent (e.g., take photo) better than chance. Löffler et al [26] also used aesthetics to design fast rotations and circular motion in a ground robot to express joy, slow rotations away from the user for sadness, jumpy movements away from the user for fear, and shaking movements toward the user for anger. They found that fear is best communicated by motion, joy is best communicated by sound plus motion, and other emotions are best communicated by color and sound.…”

Section: Design and Communicativeness Of Nonanthropomorphic Robot Motionmentioning

confidence: 99%

Communicating Dominance in a Nonanthropomorphic Robot Using Locomotion

Cuadra

Mok

et al. 2019

J. Hum.-Robot Interact.

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Dominance is a key aspect of interpersonal relationships. To what extent do nonverbal indicators related to dominance status translate to a nonanthropomorphic robot? An experiment (N = 25) addressed whether a mobile robot's motion style can influence people's perceptions of its status. Using concepts from improv theater literature, we developed two motion styles across three scenarios (robot makes lateral motions, approaches, and departs) to communicate a robot's dominance status through nonverbal expression. In agreement with the literature, participants described a motion style that was fast, in the foreground, and more animated as higher status than a motion style that was slow, in the periphery, and less animated. Participants used fewer negative emotion words to describe the robot with the purportedly high-status movements versus the purportedly low-status movements, but used more negative emotion words to describe the robot when it made departing motions that occurred in the same style. This result provides evidence that guidelines from improvisational theater for using nonverbal expression to perform interpersonal status can be applied to influence perception of a nonanthropomorphic robot's status, thus suggesting that useful models for more complicated behaviors might similarly be derived from performance literature and theory.

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Multimodal Expression of Artificial Emotion in Social Robots Using Color, Motion and Sound

Cited by 85 publications

References 34 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

Design and Evaluation of a Spherical Robot with Emotion-Like Feedback during Human-Robot Training

Communicating Dominance in a Nonanthropomorphic Robot Using Locomotion

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