A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
The study introduces a French OSCE dialogue dataset of 240 student-patient interactions, and builds a controllable LLM-based pipeline to generate synthetic OSCE dialogues. The pipeline uses retrieval-based grounding and a reflection loop for patient fidelity. A multi-level evaluation framework with LLM-as-a-Judge is proposed. Experiments show controllability modules improve patient fidelity and evaluation consistency. An interactive prototype with automatic feedback is implemented.
[2606.28526] A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
[Submitted on 26 Jun 2026]
Title:A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
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Abstract:The clinical and communication skills of medical students are commonly assessed through Objective Structured Clinical Examinations (OSCEs), which consist of brief scenario-driven simulations of doctor-patient interactions. However, training is often limited by the low availability of human standardized patients, motivating the development of realistic virtual patients (VPs). To address this gap, we introduce a French OSCE dialogue dataset comprising 240 student-patient training interactions. We build upon it a controllable LLM-based pipeline to generate synthetic OSCE dialogues. The pipeline integrates modular components, such as retrieval-based grounding and a reflection loop, to ensure patient fidelity, coherence, and realism. Additionally, we propose a multi-level evaluation framework assessing patient simulation quality, student performance, and linguistic quality, using an LLM-as-a-Judge approach. Experiments suggest that controllability modules generally improve patient fidelity and student evaluation consistency. Finally, we implement an interactive prototype in which students can practice with a VP and receive automatic feedback.
Comments: 9 pages. Accepted at SIGDIAL2026
Subjects:
Computation and Language (cs.CL); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2606.28526 [cs.CL]
(or arXiv:2606.28526v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.28526
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Doria Bonzi [view email] [v1] Fri, 26 Jun 2026 18:21:58 UTC (1,136 KB)
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