Evidence map›Paper›PMID 33680073›Full record

ArticleApplied bionics and biomechanics2021

An Evaluation of Human Conversational Preferences in Social Human-Robot Interaction.

Chapa Sirithunge, A G Buddhika P Jayasekara, D P Chandima

Abstract read
In one paragraph

Article in Applied bionics and biomechanics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Chapa SirithungeIntelligent Service Robotics Group, Department of Electrical Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka.ORCID https://orcid.org/0000-0003-3055-4920
A G Buddhika P JayasekaraIntelligent Service Robotics Group, Department of Electrical Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka.ORCID https://orcid.org/0000-0003-4678-005X
D P ChandimaIntelligent Service Robotics Group, Department of Electrical Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka.ORCID https://orcid.org/0000-0002-9440-1731

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To generate context-aware behaviors in robots, robots are required to have a careful evaluation of its encounters with humans. Unwrapping emotional hints in observable cues in an encounter will improve a robot's etiquettes in a social encounter. This article presents an extended human study conducted to examine how several factors in an encounter influence a person's preferences upon an interaction at a particular moment. We analyzed the nature of conversation preferred by a user considering the type of conversation a robot could have with its user, having the interaction initiated by the robot itself. We took an effort to explore how such preferences differ as the factors present in the surrounding alter. A social robot equipped with the capability to initiate a conversation is deployed to conduct the study by means of a wizard-of-oz (WoZ) experiment. During this study, conversational preferences of users could vary from "no interaction at all" to a "long conversation." We changed three factors in an encounter which can be different from each other in each circumstance: the audience or outsiders in the environment, user's task, and the domestic area in which the interaction takes place. Conversational preferences of users within the abovementioned conditions were analyzed in a later stage, and critical observations are highlighted. Finally, implications that could be helpful in shaping future social human-robot encounters were derived from the analysis of the results.

Identifiers

PMID33680073
PMCPMC7925063

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.