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22대 대한민국 국회 국회정보길라잡이 국회의원검색
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This study advances empathetic dialogue generation in Korean by integrating emotional learning with artificial intelligence (AI). It addresses the limited understanding of how AI-generated expressions preserve human emotional meaning. A hybrid system was developed using a fine-tuned XLM-RoBERTa model for 24-category emotion classification and ChatGPT-5 for dialogue generation, operating in context-only and emotion-aware modes. Using 18 Korean empathetic dialogue scenarios (108 utterances) from AI Hub, evaluations included exploratory data analysis, BLEU, GLEU, BERTScore, and large language model (LLM)-asa- judge assessments with five external models (ClovaX, Gemini, Perplexity, Claude, and Copilot). Emotion-aware responses were longer (133.7 ± 24.8 characters), more lexically diverse (53.7 ± 8.1 tokens), and preferred by LLM judges in 72.2% of cases, despite comparable semantic similarity (BERTScore > 0.85). The findings highlight the promise of emotion-aware AI for empathetic applications in mental health, education, and customer service, while emphasizing ethical challenges in human–AI interaction.

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