IEICE TRANSACTIONS on Information
Toward Generating Robot-Robot Natural Counseling Dialogue
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E105-D No.5 pp.928-935
- Publication Date
- 2022/05/01
- Publicized
- 2022/02/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2021DAP0008
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering and Information Management)
- Category
Authors
Tomoya HASHIGUCHI
University of Hyogo
Takehiro YAMAMOTO
University of Hyogo
Sumio FUJITA
Yahoo Japan Corporation
Hiroaki OHSHIMA
University of Hyogo
Keyword
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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},}
Copy
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 -
English
