@inproceedings{yamashita-higashinaka-2022-optimal,
title = "Optimal Summaries for Enabling a Smooth Handover in Chat-Oriented Dialogue",
author = "Yamashita, Sanae and
Higashinaka, Ryuichiro",
editor = "Hanqi, Yan and
Zonghan, Yang and
Ruder, Sebastian and
Xiaojun, Wan",
booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop",
month = nov,
year = "2022",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.aacl-srw.4",
pages = "25--31",
abstract = "In dialogue systems, one option for creating a better dialogue experience for the user is to have a human operator take over the dialogue when the system runs into trouble communicating with the user. In this type of handover situation (we call it intervention), it is useful for the operator to have access to the dialogue summary. However, it is not clear exactly what type of summary would be the most useful for a smooth handover. In this study, we investigated the optimal type of summary through experiments in which interlocutors were presented with various summary types during interventions in order to examine their effects. Our findings showed that the best summaries were an abstractive summary plus one utterance immediately before the handover and an extractive summary consisting of five utterances immediately before the handover. From the viewpoint of computational cost, we recommend that extractive summaries consisting of the last five utterances be used.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="yamashita-higashinaka-2022-optimal">
<titleInfo>
<title>Optimal Summaries for Enabling a Smooth Handover in Chat-Oriented Dialogue</title>
</titleInfo>
<name type="personal">
<namePart type="given">Sanae</namePart>
<namePart type="family">Yamashita</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ryuichiro</namePart>
<namePart type="family">Higashinaka</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yan</namePart>
<namePart type="family">Hanqi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yang</namePart>
<namePart type="family">Zonghan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sebastian</namePart>
<namePart type="family">Ruder</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Wan</namePart>
<namePart type="family">Xiaojun</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Online</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>In dialogue systems, one option for creating a better dialogue experience for the user is to have a human operator take over the dialogue when the system runs into trouble communicating with the user. In this type of handover situation (we call it intervention), it is useful for the operator to have access to the dialogue summary. However, it is not clear exactly what type of summary would be the most useful for a smooth handover. In this study, we investigated the optimal type of summary through experiments in which interlocutors were presented with various summary types during interventions in order to examine their effects. Our findings showed that the best summaries were an abstractive summary plus one utterance immediately before the handover and an extractive summary consisting of five utterances immediately before the handover. From the viewpoint of computational cost, we recommend that extractive summaries consisting of the last five utterances be used.</abstract>
<identifier type="citekey">yamashita-higashinaka-2022-optimal</identifier>
<location>
<url>https://aclanthology.org/2022.aacl-srw.4</url>
</location>
<part>
<date>2022-11</date>
<extent unit="page">
<start>25</start>
<end>31</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Optimal Summaries for Enabling a Smooth Handover in Chat-Oriented Dialogue
%A Yamashita, Sanae
%A Higashinaka, Ryuichiro
%Y Hanqi, Yan
%Y Zonghan, Yang
%Y Ruder, Sebastian
%Y Xiaojun, Wan
%S Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop
%D 2022
%8 November
%I Association for Computational Linguistics
%C Online
%F yamashita-higashinaka-2022-optimal
%X In dialogue systems, one option for creating a better dialogue experience for the user is to have a human operator take over the dialogue when the system runs into trouble communicating with the user. In this type of handover situation (we call it intervention), it is useful for the operator to have access to the dialogue summary. However, it is not clear exactly what type of summary would be the most useful for a smooth handover. In this study, we investigated the optimal type of summary through experiments in which interlocutors were presented with various summary types during interventions in order to examine their effects. Our findings showed that the best summaries were an abstractive summary plus one utterance immediately before the handover and an extractive summary consisting of five utterances immediately before the handover. From the viewpoint of computational cost, we recommend that extractive summaries consisting of the last five utterances be used.
%U https://aclanthology.org/2022.aacl-srw.4
%P 25-31
Markdown (Informal)
[Optimal Summaries for Enabling a Smooth Handover in Chat-Oriented Dialogue](https://aclanthology.org/2022.aacl-srw.4) (Yamashita & Higashinaka, AACL-IJCNLP 2022)
ACL
- Sanae Yamashita and Ryuichiro Higashinaka. 2022. Optimal Summaries for Enabling a Smooth Handover in Chat-Oriented Dialogue. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop, pages 25–31, Online. Association for Computational Linguistics.