Discourse Parsing for Multi-party Dialogues

Discourse parsing is a task which can parse discourse structure in text automatically, including identifying structure and labeling discourse relations. Most existing research of discourse parsing is about PDTB and RST-DT. However, models that trained in written datasets maybe not appropriate for spoken language and dialogues. Different from previous work on the news or monologue dataset, there is little research focuses on discourse parsing on multi-party dialogues. There are two sub-tasks in this project: edges detection and relation classification. In this project, we explore different methods for detecting discourse dependencies and discourse relations in multi-party dialogues.

 

Members:

Jiaqi Li (Graduate Student)

Wenqiang Lei (Graduate Student)

Min-Yen Kan (Professor and Advisor)