MPDD: A Multi-Party Dialogue Dataset for Analysis of Emotions and Interpersonal Relationships

Yi-Ting Chen, Hen-Hsen Huang, Hsin-Hsi Chen


Abstract
A dialogue dataset is an indispensable resource for building a dialogue system. Additional information like emotions and interpersonal relationships labeled on conversations enables the system to capture the emotion flow of the participants in the dialogue. However, there is no publicly available Chinese dialogue dataset with emotion and relation labels. In this paper, we collect the conversions from TV series scripts, and annotate emotion and interpersonal relationship labels on each utterance. This dataset contains 25,548 utterances from 4,142 dialogues. We also set up some experiments to observe the effects of the responded utterance on the current utterance, and the correlation between emotion and relation types in emotion and relation classification tasks.
Anthology ID:
2020.lrec-1.76
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
610–614
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.76
DOI:
Bibkey:
Cite (ACL):
Yi-Ting Chen, Hen-Hsen Huang, and Hsin-Hsi Chen. 2020. MPDD: A Multi-Party Dialogue Dataset for Analysis of Emotions and Interpersonal Relationships. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 610–614, Marseille, France. European Language Resources Association.
Cite (Informal):
MPDD: A Multi-Party Dialogue Dataset for Analysis of Emotions and Interpersonal Relationships (Chen et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.76.pdf