<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gervits-scheutz-2018-pardon">
    <titleInfo>
        <title>Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Felix</namePart>
        <namePart type="family">Gervits</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Matthias</namePart>
        <namePart type="family">Scheutz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Kazunori</namePart>
            <namePart type="family">Komatani</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Diane</namePart>
            <namePart type="family">Litman</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kai</namePart>
            <namePart type="family">Yu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Alex</namePart>
            <namePart type="family">Papangelis</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lawrence</namePart>
            <namePart type="family">Cavedon</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mikio</namePart>
            <namePart type="family">Nakano</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Melbourne, Australia</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Speech overlap is a common phenomenon in natural conversation and in task-oriented interactions. As human-robot interaction (HRI) becomes more sophisticated, the need to effectively manage turn-taking and resolve overlap becomes more important. In this paper, we introduce a computational model for speech overlap resolution in embodied artificial agents. The model identifies when overlap has occurred and uses timing information, dialogue history, and the agent’s goals to generate context-appropriate behavior. We implement this model in a Nao robot using the DIARC cognitive robotic architecture. The model is evaluated on a corpus of task-oriented human dialogue, and we find that the robot can replicate many of the most common overlap resolution behaviors found in the human data.</abstract>
    <identifier type="citekey">gervits-scheutz-2018-pardon</identifier>
    <identifier type="doi">10.18653/v1/W18-5011</identifier>
    <location>
        <url>https://aclanthology.org/W18-5011/</url>
    </location>
    <part>
        <date>2018-07</date>
        <extent unit="page">
            <start>99</start>
            <end>109</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents
%A Gervits, Felix
%A Scheutz, Matthias
%Y Komatani, Kazunori
%Y Litman, Diane
%Y Yu, Kai
%Y Papangelis, Alex
%Y Cavedon, Lawrence
%Y Nakano, Mikio
%S Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F gervits-scheutz-2018-pardon
%X Speech overlap is a common phenomenon in natural conversation and in task-oriented interactions. As human-robot interaction (HRI) becomes more sophisticated, the need to effectively manage turn-taking and resolve overlap becomes more important. In this paper, we introduce a computational model for speech overlap resolution in embodied artificial agents. The model identifies when overlap has occurred and uses timing information, dialogue history, and the agent’s goals to generate context-appropriate behavior. We implement this model in a Nao robot using the DIARC cognitive robotic architecture. The model is evaluated on a corpus of task-oriented human dialogue, and we find that the robot can replicate many of the most common overlap resolution behaviors found in the human data.
%R 10.18653/v1/W18-5011
%U https://aclanthology.org/W18-5011/
%U https://doi.org/10.18653/v1/W18-5011
%P 99-109

Markdown (Informal)

[Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents](https://aclanthology.org/W18-5011/) (Gervits & Scheutz, SIGDIAL 2018)

• Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents (Gervits & Scheutz, SIGDIAL 2018)

ACL

• Felix Gervits and Matthias Scheutz. 2018. Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 99–109, Melbourne, Australia. Association for Computational Linguistics.