Who You Are, What You Say: Intra- and Inter- Context Personality for Emotion Recognition in Conversation (2026.findings-eacl)
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| Challenge: | Existing approaches to Emotion Recognition in conversation (ERC) focus on modeling speaker dynamics within dialogues. |
| Approach: | They propose a personality-aware ERC framework that segregates conversational context into intra- and inter-speaker components and models static or dynamic personality traits to represent stable and evolving speaker dispositions. |
| Outcome: | The proposed framework improves weighted F1 by 2.74% over non-LLM methods and 0.98% over recent LLM-based methods. |
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| Challenge: | Emotion Recognition in Conversation (ERC) aims to analyze the speaker’s emotional state in a conversation. |
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| Challenge: | Emotion recognition in conversation (ERC) is an advanced capability of conversational AI systems. |
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| Challenge: | Emotion recognition in conversations (ERC) is a task that aims to recognize the emotion of each utterance in conversations. |
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