Effects of Colored LEDs in Robotic Storytelling on Storytelling Experience and Robot Perception

Steinhaeusser, Sophia C.; Lugrin, Birgit

doi:10.1109/hri53351.2022.9889469

Cited by 4 publications

(1 citation statement)

References 34 publications

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“…This involved including non-binary options or allowing for non-reporting explicitly (17, 3.4%) as well as being considerate of participants' privacy (35, 7%). For example, Steinhaeusser and Lugrin [95] reported on a participant who "self-reported as diverse gender," which is gender-expansive as well as considerate of privacy, with no specific gender details reported. Nevertheless, 106 studies (21.1%) relied on a gender binary approach.…”

Section: Sex and Gendermentioning

confidence: 99%

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Seaborn

Barbareschi

Chandra

2023

Int J of Soc Robotics

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Critical voices within and beyond the scientific community have pointed to a grave matter of concern regarding who is included in research and who is not. Subsequent investigations have revealed an extensive form of sampling bias across a broad range of disciplines that conduct human subjects research called “WEIRD”: Western, Educated, Industrial, Rich, and Democratic. Recent work has indicated that this pattern exists within human–computer interaction (HCI) research, as well. How then does human–robot interaction (HRI) fare? And could there be other patterns of sampling bias at play, perhaps those especially relevant to this field of study? We conducted a systematic review of the premier ACM/IEEE International Conference on Human-Robot Interaction (2006–2022) to discover whether and how WEIRD HRI research is. Importantly, we expanded our purview to other factors of representation highlighted by critical work on inclusion and intersectionality as potentially underreported, overlooked, and even marginalized factors of human diversity. Findings from 827 studies across 749 papers confirm that participants in HRI research also tend to be drawn from WEIRD populations. Moreover, we find evidence of limited, obscured, and possible misrepresentation in participant sampling and reporting along key axes of diversity: sex and gender, race and ethnicity, age, sexuality and family configuration, disability, body type, ideology, and domain expertise. We discuss methodological and ethical implications for recruitment, analysis, and reporting, as well as the significance for HRI as a base of knowledge.

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Section: Sex and Gendermentioning

confidence: 99%

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Seaborn

Barbareschi

Chandra

2023

Int J of Soc Robotics

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Towards the development of an automated robotic storyteller: comparing approaches for emotional story annotation for non-verbal expression via body language

Steinhaeusser,

Zehe,

Schnetter

et al. 2024

J Multimodal User Interfaces

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Storytelling is a long-established tradition and listening to stories is still a popular leisure activity. Caused by technization, storytelling media expands, e.g., to social robots acting as multi-modal storytellers, using different multimodal behaviours such as facial expressions or body postures. With the overarching goal to automate robotic storytelling, we have been annotating stories with emotion labels which the robot can use to automatically adapt its behavior. With it, three different approaches are compared in two studies in this paper: 1) manual labels by human annotators (MA), 2) software-based word-sensitive annotation using the Linguistic Inquiry and Word Count program (LIWC), and 3) a machine learning based approach (ML). In an online study showing videos of a storytelling robot, the annotations were validated, with LIWC and MA achieving the best, and ML the worst results. In a laboratory user study, the three versions of the story were compared regarding transportation and cognitive absorption, revealing no significant differences but a positive trend towards MA. On this empirical basis, the Automated Robotic Storyteller was implemented using manual annotations. Future iterations should include other robots and modalities, fewer emotion labels and their probabilities.

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Integrating sound effects and background music in Robotic storytelling – A series of online studies across different story genres

Steinhaeusser,

Lugrin

2024

Computers in Human Behavior: Artificial Humans

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Effects of Colored LEDs in Robotic Storytelling on Storytelling Experience and Robot Perception

Cited by 4 publications

References 34 publications

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Towards the development of an automated robotic storyteller: comparing approaches for emotional story annotation for non-verbal expression via body language

Integrating sound effects and background music in Robotic storytelling – A series of online studies across different story genres

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