"Thank You for Sharing that Interesting Fact!" Effects of Capability and Context on Indirect Speech Act Use in Task-Based Human-Robot Dialogue

Naturally interacting robots must be able to understand natural human speech. As such, recent work has sought to allow robots to infer the intentions behind commonly used non-literal utterances such as indirect speech acts (ISAs). However, it is still unclear to what extent ISAs will actually be use...

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Vydáno v:2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI) s. 298 - 306
Hlavní autoři: Williams, Tom, Thames, Daria, Novakoff, Julia, Scheutz, Matthias
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: New York, NY, USA ACM 26.02.2018
Edice:ACM Conferences
Témata:
Computing methodologies > Artificial intelligence > Natural language processing > Discourse, dialogue and pragmatics
Human perceptions of robot communications
Human-centered computing > Human computer interaction (HCI) > HCI design and evaluation methods > Laboratory experiments
Human-centered computing > Human computer interaction (HCI) > HCI design and evaluation methods > User studies
Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Natural language interfaces
Human-robot interaction
Intention understanding
Robots
Speech act theory
Systematics
Task analysis
Task-based human-robot dialogue
intention understanding
task-based human-robot dialogue
human perceptions of robot communications
speech act theory
ISBN:9781450349536, 1450349536
ISSN:2167-2148
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Shrnutí:Naturally interacting robots must be able to understand natural human speech. As such, recent work has sought to allow robots to infer the intentions behind commonly used non-literal utterances such as indirect speech acts (ISAs). However, it is still unclear to what extent ISAs will actually be used in task-based human-robot dialogue, and to what extent robots could function without the ability to understand ISAs. In this paper, we present the results of a Wizard-of-Oz experiment that examined human ISA use in scenarios that did or did not have conventionalized social norms, and analyzed both ISA use and perceptions of robots when robots were or were not capable of understanding ISAs. Our results suggest that (1) ISAs are commonly used in task-based human-robot dialogues, even when robots show themselves unable to understand ISAs; (2) ISA use is more common in contexts with conventionalized social norms; and (3) a robot's inability to understand ISAs harms both the robot's task performance and human perception of the robot.
ISBN:9781450349536
1450349536
ISSN:2167-2148
DOI:10.1145/3171221.3171246