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With a Little Help from my (Linguistic) Friends: Topic Segmentation of Multi-party Casual Conversations

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arxiv 2402.02837 v1 pith:FMYFUPXH submitted 2024-02-05 cs.CL

classification cs.CL
keywords structuretopicapproachconversationconversationsdialoguehelplevel
verification ladder T0 review T1 audit T2 compute T3 formal
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Topics play an important role in the global organisation of a conversation as what is currently discussed constrains the possible contributions of the participant. Understanding the way topics are organised in interaction would provide insight on the structure of dialogue beyond the sequence of utterances. However, studying this high-level structure is a complex task that we try to approach by first segmenting dialogues into smaller topically coherent sets of utterances. Understanding the interactions between these segments would then enable us to propose a model of topic organisation at a dialogue level. In this paper we work with open-domain conversations and try to reach a comparable level of accuracy as recent machine learning based topic segmentation models but with a formal approach. The features we identify as meaningful for this task help us understand better the topical structure of a conversation.

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    cs.CL 2025-05 conditional novelty 4.0 of 10

    LLMs can produce fluent movie reviews that readers often mistake for human-written ones, but the models differ in emotional balance and depth.

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