Publications
JOURNAL (INTERNATIONAL) Toward Generating Robot-Robot Natural Counseling Dialogue
Tomoya HASHIGUCHI (Hyogo univ.), Takehiro YAMAMOTO (Hyogo univ.), Sumio FUJITA, Hiroaki OHSHIMA (Hyogo univ.)
IEICE TRANSACTIONS on Information and Systems (IEICE TRANSACTIONS)
February 07, 2022
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.
Paper : Toward Generating Robot-Robot Natural Counseling Dialogue (external link)