Annotating Coherence Relations for Studying Topic Transitions in Social Talk
This study develops the strand of research on topic transitions in social talk which aims to gain a better understanding of interlocutors’ conversational goals. Lưu and Malamud (2020) proposed that one way to identify such transitions is to annotate coherence relations, and then to identify utterances potentially expressing new topics as those that fail to participate in these relations. This work validates and refines their suggested annotation methodology, focusing on annotating most prominent coherence relations in face-to-face social dialogue. The result is a publicly accessible gold standard corpus with efficient and reliable annotation, whose broad coverage provides a foundation for future steps of identifying and classifying new topic utterances.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Towards Coherent and Captivating Topic Transitions in Knowledge-Grounded Conversations
Knowledge-grounded conversations require skillful usage of knowledge to generate suitably diverse responses to keep user captivated while maintaining coherence to the dialogue context. However, current approaches that di…
CobSeg: Coherence Boundary Modeling for Dialogue Topic Segmentation
Dialogue topic segmentation is critical in many human-AI collaborative applications which requires identifying heterogeneous boundary cues, including lexical transitions near utterance edges and semantic discontinuities …
Annotation of anaphoric relations and topic continuity in Japanese conversation
This paper proposes a basic scheme for annotating anaphoric relations in Japanese conversations. More specifically, we propose methods of (i) dividing discourse segments into meaningful units, (ii) identifying zero prono…
Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment
Current models of dialogue mainly focus on utterances within a topically coherent discourse segment, rather than new-topic utterances (NTUs), which begin a new topic not correlating with the content of prior discourse. A…
General ClassificationCrowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task
The perspective of being able to crowd-source coherence relations bears the promise of acquiring annotations for new texts quickly, which could then increase the size and variety of discourse-annotated corpora. It would …
RelationVocal Bursts Valence Prediction