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LLM-Anchored Paralinguistic Enrichment is proposed, which enriches LLM-derived linguistic representations with paralinguistic cues through three coordinated innovations that achieves state-of-the-art performance across all four primary settings.
EmoDialogue, a bilingual dataset providing necessary fine-grained supervision through response pairs with rigorously defined EI gradations, and EmoS, a specialized evaluator model optimized via Supervised Fine-Tuning and Group Relative Policy Optimization, are introduced, establishing a foundational framework for advan...
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