The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cette étude, nous générons des contenus de dialogue dans lesquels deux systèmes discutent de leur détresse. L'utilisateur saisit des phrases qui incluent l'environnement et les sentiments de détresse. Le système génère le contenu du dialogue à partir de l'entrée. Dans cette étude, nous avons créé des données de dialogue sur la détresse afin de les générer grâce au deep learning. Le modèle génératif affine le GPT du modèle pré-entraîné à l'aide de la méthode TransferTransfo. La contribution de cette étude est la création d'un ensemble de données conversationnelles utilisant des données accessibles au public. Cette étude a utilisé EmpatheticDialogues, un ensemble de données de dialogue empathique existant, et Reddit r/offmychest, un ensemble de données publiques sur la détresse. Les modèles affinés avec chaque donnée ont été évalués à la fois automatiquement (par exemple par les scores BLEU et ROUGE) et manuellement (par exemple par pertinence et empathie) par des évaluateurs humains.
Tomoya HASHIGUCHI
University of Hyogo
Takehiro YAMAMOTO
University of Hyogo
Sumio FUJITA
Yahoo Japan Corporation
Hiroaki OHSHIMA
University of Hyogo
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Tomoya HASHIGUCHI, Takehiro YAMAMOTO, Sumio FUJITA, Hiroaki OHSHIMA, "Toward Generating Robot-Robot Natural Counseling Dialogue" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 5, pp. 928-935, May 2022, doi: 10.1587/transinf.2021DAP0008.
Abstract: In this study, we generate dialogue contents in which two systems discuss their distress with each other. The user inputs sentences that include environment and feelings of distress. The system generates the dialogue content from the input. In this study, we created dialogue data about distress in order to generate them using deep learning. The generative model fine-tunes the GPT of the pre-trained model using the TransferTransfo method. The contribution of this study is the creation of a conversational dataset using publicly available data. This study used EmpatheticDialogues, an existing empathetic dialogue dataset, and Reddit r/offmychest, a public data set of distress. The models fine-tuned with each data were evaluated both automatically (such as by the BLEU and ROUGE scores) and manually (such as by relevance and empathy) by human assessors.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021DAP0008/_p
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@ARTICLE{e105-d_5_928,
author={Tomoya HASHIGUCHI, Takehiro YAMAMOTO, Sumio FUJITA, Hiroaki OHSHIMA, },
journal={IEICE TRANSACTIONS on Information},
title={Toward Generating Robot-Robot Natural Counseling Dialogue},
year={2022},
volume={E105-D},
number={5},
pages={928-935},
abstract={In this study, we generate dialogue contents in which two systems discuss their distress with each other. The user inputs sentences that include environment and feelings of distress. The system generates the dialogue content from the input. In this study, we created dialogue data about distress in order to generate them using deep learning. The generative model fine-tunes the GPT of the pre-trained model using the TransferTransfo method. The contribution of this study is the creation of a conversational dataset using publicly available data. This study used EmpatheticDialogues, an existing empathetic dialogue dataset, and Reddit r/offmychest, a public data set of distress. The models fine-tuned with each data were evaluated both automatically (such as by the BLEU and ROUGE scores) and manually (such as by relevance and empathy) by human assessors.},
keywords={},
doi={10.1587/transinf.2021DAP0008},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - Toward Generating Robot-Robot Natural Counseling Dialogue
T2 - IEICE TRANSACTIONS on Information
SP - 928
EP - 935
AU - Tomoya HASHIGUCHI
AU - Takehiro YAMAMOTO
AU - Sumio FUJITA
AU - Hiroaki OHSHIMA
PY - 2022
DO - 10.1587/transinf.2021DAP0008
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2022
AB - In this study, we generate dialogue contents in which two systems discuss their distress with each other. The user inputs sentences that include environment and feelings of distress. The system generates the dialogue content from the input. In this study, we created dialogue data about distress in order to generate them using deep learning. The generative model fine-tunes the GPT of the pre-trained model using the TransferTransfo method. The contribution of this study is the creation of a conversational dataset using publicly available data. This study used EmpatheticDialogues, an existing empathetic dialogue dataset, and Reddit r/offmychest, a public data set of distress. The models fine-tuned with each data were evaluated both automatically (such as by the BLEU and ROUGE scores) and manually (such as by relevance and empathy) by human assessors.
ER -