构建波斯语心理治疗对话数据集，支持基于大模型的共情式对话。
HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents
- 用大模型角色扮演模拟波斯语患者真实心理对话。
- 人类评估显示其共情、连贯性与真实感优于现有基线。
- 适合研究跨文化心理支持与生成式AI在心理健康中的应用。
我们提出HamRaz，一个基于人本疗法（PCT）的波斯语文化适配对话数据集，用于AI辅助心理健康支持。为反映真实治疗挑战，结合脚本化对话与自适应大语言模型（LLM）角色扮演，捕捉波斯语使用者在情感与语义上的模糊性与复杂性。我们引入HamRazEval，一种双框架评估体系，涵盖通用指标与专业心理关系度量。人工评估表明，HamRaz在共情、连贯性与真实性方面优于现有基线。该资源推动数字人文发展，弥合语言、文化与心理健康在代表性不足群体中的鸿沟。
原文摘要 · Abstract (English)
We present HamRaz, a culturally adapted Persian-language dataset for AI-assisted mental health support, grounded in Person-Centered Therapy (PCT). To reflect real-world therapeutic challenges, we combine script-based dialogue with adaptive large language models (LLM) role-playing, capturing the ambiguity and emotional nuance of Persian-speaking clients. We introduce HamRazEval, a dual-framework for assessing conversational and therapeutic quality using General Metrics and specialized psychological relationship measures. Human evaluations show HamRaz outperforms existing baselines in empathy, coherence, and realism. This resource contributes to the Digital Humanities by bridging language, culture, and mental health in underrepresented communities.
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