How People Talk with Robots: Designing Dialogue to Reduce User Uncertainty

Fischer, Kerstin

doi:10.1609/aimag.v32i4.2377

Cited by 40 publications

(25 citation statements)

References 31 publications

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“…In a follow-up study, we utilised robots with strikingly different embodiments in the same scenario with the same behaviour set borrowed from hearing dogs. We showed that the appearance of the robot has only minor effect on how humans recognize the goal directed behaviour ('intent') of these robots , supporting earlier results found by Fischer (2011).…”

Section: The Problem Of Resemblancesupporting

confidence: 89%

Why is a dog-behaviour-inspired social robot not a doggy-robot?

Faragó

Gácsi

Korcsok

et al. 2014

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Section: The Problem Of Resemblancesupporting

confidence: 89%

Why is a dog-behaviour-inspired social robot not a doggy-robot?

Faragó

Gácsi

Korcsok

et al. 2014

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“…The design choices for the dialog interface of our PbD system are influenced by work on spoken interactions with robots within the human-robot interaction (HRI) literature [7,8,21]. Work in the field of human-computer interaction which investigate how the system feedback influences human input [9,16,6] also have implications for human-robot dialog, and have been considered in the design of our system.…”

Section: Related Workmentioning

confidence: 99%

Teaching people how to teach robots

Çakmak

Takayama

2014

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

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Allowing end-users to harness the full capability of general purpose robots, requires giving them powerful tools. As the functionality of these tools increase, learning how to use them becomes more challenging. In this paper we investigate the use of instructional materials to support the learnability of a Programming by Demonstration tool. We develop a system that allows users to program complex manipulation skills on a two-armed robot through a spoken dialog interface and by physically moving the robot's arms. We present a user study (N=30) in which participants are left alone with the robot and a user manual, without any prior instructions on how to program the robot. Instead, they are asked to figure it out on their own. We investigate the effect of providing users with an additional written tutorial or an instructional video. We find that videos are most effective in training the user; however, this effect might be superficial and ultimately trial-and-error plays an important role in learning to program the robot. We also find that tutorials can be problematic when the interaction has uncertainty due to speech recognition errors. Overall, the user study demonstrates the effectiveness and learnability of the our system, while providing useful feedback about the dialog design.

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“…Extrapolating from previous work in human–computer interaction suggests that people may involuntarily and automatically interact with robots like they interact with humans (Reeves & Nass, ). Instead, comparisons between child‐directed and robot‐directed speech in this project revealed interaction to be mainly based on participants' perceptions of the robot's affordances (Fischer, ). Users' preconceptions also influence their interactions with robots considerably, guiding them to a particular understanding of the situation (Fischer, ).…”

Section: How Humans Talk To Robots (And Why)mentioning

confidence: 96%

The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning

Broz¹,

Nehaniv²,

Belpaeme³

et al. 2014

Topics in Cognitive Science

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This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots.

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How People Talk with Robots: Designing Dialogue to Reduce User Uncertainty

Cited by 40 publications

References 31 publications

Why is a dog-behaviour-inspired social robot not a doggy-robot?

Why is a dog-behaviour-inspired social robot not a doggy-robot?

Teaching people how to teach robots

The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning

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