DraDDP: A Multimodal Multi-Party Dialogue Discourse Parsing Dataset
DraDDP introduces the first multimodal dataset for multi-party dialogue discourse parsing, addressing limitations in existing textual-only and two-party models.
The DraDDP dataset provides a framework for identifying dependency structures and relation types in complex, multi-party conversations. By incorporating multimodal data, it enables researchers to better analyze discourse in settings that mirror real-world interactions, moving beyond the constraints of traditional two-party textual analysis.