@inproceedings{abbasi-etal-2025-hamraz,
title = "{H}am{R}az: A Culture-Based {P}ersian Conversation Dataset for Person-Centered Therapy Using {LLM} Agents",
author = "Abbasi, Mohammad Amin and
Mirnezami, Farnaz Sadat and
Neshati, Ali and
Naderi, Hassan",
editor = "Arachchige, Isuri Nanomi and
Frontini, Francesca and
Mitkov, Ruslan and
Rayson, Paul",
booktitle = "Proceedings of the First on Natural Language Processing and Language Models for Digital Humanities",
month = sep,
year = "2025",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2025.lm4dh-1.1/",
pages = "1--24",
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."
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<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.</abstract>
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%0 Conference Proceedings
%T HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents
%A Abbasi, Mohammad Amin
%A Mirnezami, Farnaz Sadat
%A Neshati, Ali
%A Naderi, Hassan
%Y Arachchige, Isuri Nanomi
%Y Frontini, Francesca
%Y Mitkov, Ruslan
%Y Rayson, Paul
%S Proceedings of the First on Natural Language Processing and Language Models for Digital Humanities
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F abbasi-etal-2025-hamraz
%X 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.
%U https://aclanthology.org/2025.lm4dh-1.1/
%P 1-24
Markdown (Informal)
[HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents](https://aclanthology.org/2025.lm4dh-1.1/) (Abbasi et al., LM4DH 2025)
ACL