HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents

Mohammad Amin Abbasi, Farnaz Sadat Mirnezami, Ali Neshati, Hassan Naderi


Abstract
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 real-ism. This resource contributes to the Digital Humanities by bridging language, culture, and mental health in underrepresented communities.
Anthology ID:
2025.lm4dh-1.1
Volume:
Proceedings of the First on Natural Language Processing and Language Models for Digital Humanities
Month:
September
Year:
2025
Address:
Varna, Bulgaria
Editors:
Isuri Nanomi Arachchige, Francesca Frontini, Ruslan Mitkov, Paul Rayson
Venues:
LM4DH | WS
SIG:
Publisher:
INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:
1–24
Language:
URL:
https://aclanthology.org/2025.lm4dh-1.1/
DOI:
Bibkey:
Cite (ACL):
Mohammad Amin Abbasi, Farnaz Sadat Mirnezami, Ali Neshati, and Hassan Naderi. 2025. HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents. In Proceedings of the First on Natural Language Processing and Language Models for Digital Humanities, pages 1–24, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents (Abbasi et al., LM4DH 2025)
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PDF:
https://aclanthology.org/2025.lm4dh-1.1.pdf