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New research models turn-taking dynamics in multi-party conversations

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore the dynamics of multi-party conversations, focusing on how turn-taking and conversational cues can be modeled and predicted. The first paper introduces a multi-task learning approach that uses "turn-transition entropy" to improve intent recognition by analyzing speaker transitions. The second paper investigates how gaze and speech dynamics, along with interpersonal closeness, signal conversational floor changes, achieving a ROC AUC of 0.76 with a combination of gaze and loudness features. AI

IMPACT These studies offer new methods for understanding and predicting conversational dynamics, potentially improving dialogue systems and human-computer interaction.

RANK_REASON Two academic papers published on arXiv detailing novel methods for analyzing multi-party conversations.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New research models turn-taking dynamics in multi-party conversations

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Two academic papers published on arXiv detailing novel methods for analyzing multi-party conversations.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Galo Castillo-L\'opez, Alexis Lombard, Ga\"el de Chalendar, Nasredine Semmar ·

    Leveraging Turn-taking Dynamics for Intent Recognition in Multi-party Conversations

    arXiv:2608.28926v1 Announce Type: new Abstract: We propose a multi-task learning approach for multi-party dialogue intent recognition that leverages an auxiliary task that models turn-taking dynamics. Specifically, we introduce turn-transition entropy, a self-supervised target co…

  2. arXiv cs.CL TIER_1 English(EN) · Mark Dourado, Karim Haddad, Henrik G. Hassager, Stefania Serafin ·

    Predicting Turn-Taking Outcomes in Multi-Party Conversation: Interpretable Modelling of Speech and Gaze Dynamics with Interpersonal Closeness

    arXiv:2608.27988v1 Announce Type: new Abstract: Smooth speaker transitions are fundamental to effective conversation and rely on an interlocutor's ability to predict when to enter the conversation. This ability depends on accurately interpreting and expressing the verbal and non-…

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