Hearing a Nose?

Mara, Martina; Schreibelmayr, Simon; Berger, Franz

doi:10.1145/3371382.3378285

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…When people think of robots, they usually have an image of a human-like machine in their minds: an apparatus with arms, legs, and a head, covered in metal or possibly silicone skin (see Cave et al, 2020; Mara et al, 2020). Even though such robots hardly, if at all, exist in our everyday lives, media reports about engineering advancements and science fiction stories about the – sometimes more, sometimes less peaceful – relationship between humans and their robotic counterparts have long made us wonder what it would be like if humanoid machines were really among us.…”

Section: Human-like Robotsmentioning

confidence: 99%

Human-Like Robots and the Uncanny Valley

Mara

Appel

Gnambs

2022

Zeitschrift für Psychologie

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Abstract. In the field of human-robot interaction, the well-known uncanny valley hypothesis proposes a curvilinear relationship between a robot’s degree of human likeness and the observers’ responses to the robot. While low to medium human likeness should be associated with increased positive responses, a shift to negative responses is expected for highly anthropomorphic robots. As empirical findings on the uncanny valley hypothesis are inconclusive, we conducted a random-effects meta-analysis of 49 studies (total N = 3,556) that reported 131 evaluations of robots based on the Godspeed scales for anthropomorphism (i.e., human likeness) and likeability. Our results confirm more positive responses for more human-like robots at low to medium anthropomorphism, with moving robots rated as more human-like but not necessarily more likable than static ones. However, because highly anthropomorphic robots were sparsely utilized in previous studies, no conclusions regarding proposed adverse effects at higher levels of human likeness can be made at this stage.

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Section: Human-like Robotsmentioning

confidence: 99%

Human-Like Robots and the Uncanny Valley

Mara

Appel

Gnambs

2022

Zeitschrift für Psychologie

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“…Gong and Lai [62] found that mixing a human voice with a TTS at the same time led to poorer performance, even though people thought that they had performed better and found that version of the system easier to use. In a novel approach to exploring perceived embodiment, Mara et al [107] had participants draw the body based on the voice, finding that humanlike voices were given ears, eyes, and noses, and synthetic voices were given wheels.…”

Section: Anthropomorphism Humanlikeness and Natural Vs Synthetic Voicesmentioning

confidence: 99%

“…Manipulation and perception checks of designed features should become a staple of research designs. Explorations of voice and body can use audiovisual matching checks or even having participants draw the body from the voice [107]. Further, these should be done before the final study or prototype version as well as after other measures have been collected to avoid unintended effects, such as stereotype threats [168].…”

Section: Incorporation Of Rigorous and Relevantmentioning

confidence: 99%

Voice in Human–Agent Interaction

Seaborn

Miyake

Pennefather³

et al. 2021

ACM Comput. Surv.

103

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Social robots, conversational agents, voice assistants, and other embodied AI are increasingly a feature of everyday life. What connects these various types of intelligent agents is their ability to interact with people through voice. Voice is becoming an essential modality of embodiment, communication, and interaction between computer-based agents and end-users. This survey presents a meta-synthesis on agent voice in the design and experience of agents from a human-centered perspective: voice-based human--agent interaction (vHAI). Findings emphasize the social role of voice in HAI as well as circumscribe a relationship between agent voice and body, corresponding to human models of social psychology and cognition. Additionally, changes in perceptions of and reactions to agent voice over time reveals a generational shift coinciding with the commercial proliferation of mobile voice assistants. The main contributions of this work are a vHAI classification framework for voice across various agent forms, contexts, and user groups, a critical analysis grounded in key theories, and an identification of future directions for the oncoming wave of vocal machines.

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Audio–Visual Predictive Processing in the Perception of Humans and Robots

Sarigul

Ürgen

2023

Int J of Soc Robotics

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Recent work in cognitive science suggests that our expectations affect visual perception. With the rise of artificial agents in human life in the last few decades, one important question is whether our expectations about non-human agents such as humanoid robots affect how we perceive them. In the present study, we addressed this question in an audio–visual context. Participants reported whether a voice embedded in a noise belonged to a human or a robot. Prior to this judgment, they were presented with a human or a robot image that served as a cue and allowed them to form an expectation about the category of the voice that would follow. This cue was either congruent or incongruent with the category of the voice. Our results show that participants were faster and more accurate when the auditory target was preceded by a congruent cue than an incongruent cue. This was true regardless of the human-likeness of the robot. Overall, these results suggest that our expectations affect how we perceive non-human agents and shed light on future work in robot design.

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Hearing a Nose?

Cited by 5 publications

References 6 publications

Human-Like Robots and the Uncanny Valley

Human-Like Robots and the Uncanny Valley

Voice in Human–Agent Interaction

Audio–Visual Predictive Processing in the Perception of Humans and Robots

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