@inproceedings{pragst-ultes-2018-changing,
title = "Changing the Level of Directness in Dialogue using Dialogue Vector Models and Recurrent Neural Networks",
author = "Pragst, Louisa and
Ultes, Stefan",
editor = "Komatani, Kazunori and
Litman, Diane and
Yu, Kai and
Papangelis, Alex and
Cavedon, Lawrence and
Nakano, Mikio",
booktitle = "Proceedings of the 19th Annual {SIG}dial Meeting on Discourse and Dialogue",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-5002",
doi = "10.18653/v1/W18-5002",
pages = "11--19",
abstract = "In cooperative dialogues, identifying the intent of ones conversation partner and acting accordingly is of great importance. While this endeavour is facilitated by phrasing intentions as directly as possible, we can observe in human-human communication that a number of factors such as cultural norms and politeness may result in expressing one{'}s intent indirectly. Therefore, in human-computer communication we have to anticipate the possibility of users being indirect and be prepared to interpret their actual meaning. Furthermore, a dialogue system should be able to conform to human expectations by adjusting the degree of directness it uses to improve the user experience. To reach those goals, we propose an approach to differentiate between direct and indirect utterances and find utterances of the opposite characteristic that express the same intent. In this endeavour, we employ dialogue vector models and recurrent neural networks.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="pragst-ultes-2018-changing">
<titleInfo>
<title>Changing the Level of Directness in Dialogue using Dialogue Vector Models and Recurrent Neural Networks</title>
</titleInfo>
<name type="personal">
<namePart type="given">Louisa</namePart>
<namePart type="family">Pragst</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stefan</namePart>
<namePart type="family">Ultes</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>In cooperative dialogues, identifying the intent of ones conversation partner and acting accordingly is of great importance. While this endeavour is facilitated by phrasing intentions as directly as possible, we can observe in human-human communication that a number of factors such as cultural norms and politeness may result in expressing one’s intent indirectly. Therefore, in human-computer communication we have to anticipate the possibility of users being indirect and be prepared to interpret their actual meaning. Furthermore, a dialogue system should be able to conform to human expectations by adjusting the degree of directness it uses to improve the user experience. To reach those goals, we propose an approach to differentiate between direct and indirect utterances and find utterances of the opposite characteristic that express the same intent. In this endeavour, we employ dialogue vector models and recurrent neural networks.</abstract>
<identifier type="citekey">pragst-ultes-2018-changing</identifier>
<identifier type="doi">10.18653/v1/W18-5002</identifier>
<location>
<url>https://aclanthology.org/W18-5002</url>
</location>
<part>
<date>2018-07</date>
<extent unit="page">
<start>11</start>
<end>19</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Changing the Level of Directness in Dialogue using Dialogue Vector Models and Recurrent Neural Networks
%A Pragst, Louisa
%A Ultes, Stefan
%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 pragst-ultes-2018-changing
%X In cooperative dialogues, identifying the intent of ones conversation partner and acting accordingly is of great importance. While this endeavour is facilitated by phrasing intentions as directly as possible, we can observe in human-human communication that a number of factors such as cultural norms and politeness may result in expressing one’s intent indirectly. Therefore, in human-computer communication we have to anticipate the possibility of users being indirect and be prepared to interpret their actual meaning. Furthermore, a dialogue system should be able to conform to human expectations by adjusting the degree of directness it uses to improve the user experience. To reach those goals, we propose an approach to differentiate between direct and indirect utterances and find utterances of the opposite characteristic that express the same intent. In this endeavour, we employ dialogue vector models and recurrent neural networks.
%R 10.18653/v1/W18-5002
%U https://aclanthology.org/W18-5002
%U https://doi.org/10.18653/v1/W18-5002
%P 11-19
Markdown (Informal)
[Changing the Level of Directness in Dialogue using Dialogue Vector Models and Recurrent Neural Networks](https://aclanthology.org/W18-5002) (Pragst & Ultes, SIGDIAL 2018)
ACL