The distribution of discourse relations within and across turns in spontaneous conversation
This work addresses the problem of understanding discourse relations in spontaneous conversation for linguistics and NLP researchers, but it is incremental as it adapts existing methods to a new context.
The study adapted a system of discourse relations for written language to spontaneous dialogue using crowdsourced annotations, finding that different discourse contexts produce distinct distributions of discourse relations, with single-turn annotations creating the most uncertainty for annotators.
Time pressure and topic negotiation may impose constraints on how people leverage discourse relations (DRs) in spontaneous conversational contexts. In this work, we adapt a system of DRs for written language to spontaneous dialogue using crowdsourced annotations from novice annotators. We then test whether discourse relations are used differently across several types of multi-utterance contexts. We compare the patterns of DR annotation within and across speakers and within and across turns. Ultimately, we find that different discourse contexts produce distinct distributions of discourse relations, with single-turn annotations creating the most uncertainty for annotators. Additionally, we find that the discourse relation annotations are of sufficient quality to predict from embeddings of discourse units.