Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition
arXiv cs.CL 6 hours ago
Researchers developed a dialogue summarization framework that models both semantic content and emotion dynamics using a hierarchical Chain-of-Agents approach that decomposes conversations by topic segments and participant-specific utterances. The method was evaluated on multimodal dialogue datasets using small language models and introduces new emotion trajectory metrics to measure how well summaries preserve emotional flow across conversations. The framework enables more accurate dialogue summarization that captures both informational content and emotional progression, moving beyond existing approaches that treat dialogue like monologic text.