MPDD: A multi-party dialogue dataset for analysis of emotions and interpersonal relationships
Journal
LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings
Pages
610-614
Date Issued
2020
Author(s)
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. ? European Language Resources Association (ELRA), licensed under CC-BY-NC
Subjects
Dialogue systems; Indispensable resources; Interpersonal relationship; Multi-party dialogues; Relation classifications; Speech processing
Type
conference paper