SIMAX: A Scalable and Interpretable Framework for Multi-Fidelity and Annotated Clinician-Patient Dialogue Simulation

Source

• Source name: arXiv
• Source kind: paper
• Authors / organization: Zhuhan Bao, Rui Yang, Bohao Yang, Zhiyi Liu, Sicheng Shu, Ruio Heerschap, Le Li, Doris Yang, Elisabeth Bond, Haoyuan Wang, Nicoleta Economou-Zavlanos, Joshua M. Biro, Matthew McDermott, Nan Liu, Anand Chowdhury, Kai Sun, Kathryn Pollak, Ed Hammond, Chuan Hong
• Venue: arXiv: cs.CL
• Published: 2026-06-29
• Collected: 2026-06-30
• URL: http://arxiv.org/abs/2606.30491v1
• PDF: https://arxiv.org/pdf/2606.30491v1
• DOI: UNKNOWN

Plain-Language Brief

The study introduces SIMAX, a framework that generates controlled clinical dialogue data with reference behavioral annotations for evaluating AI-driven communication coding systems. The generated dialogues are of reasonable speech naturalness, high transcription fidelity, and positive text-audio correspondence according to automated assessments, and have a median MOS of 4.67 and a median clinical realism score of 3.00 from human evaluation.

What the Document Says

• The study introduces SIMAX, a framework for generating controlled clinician-patient dialogues.
• SIMAX generates dialogues from predefined scenarios, personas, voice conditions, and target communication behaviors.
• Behaviors are controlled using two codebooks: the Global Codebook and the WISER Codebook.
• The study evaluated SIMAX using automated and human quality assessments.
• SIMAX generated 3,388 dialogues across three specialties, multiple visit stages, persona characteristics, and accent conditions.
• Automated assessment results include mean UTMOS and WV-MOS scores, WER and CER, and CLAP cosine similarity.
• The human evaluation showed a median MOS of 4.67 and a median clinical realism score of 3.00.
• Downstream evaluation suggests SIMAX can assess the response of communication coding systems to behavioral targets.

Key Concepts Mentioned

• SIMAX
• clinician-patient dialogues
• communication behaviors
• automated assessment
• human evaluation
• downstream evaluation

Claims Made by the Document

• SIMAX generates controlled and reproducible simulated clinician-patient dialogues.
• SIMAX can assess how a communication coding system responds to behavioral targets.

Evidence Used

• Results section of the study

Methods / Approach

UNKNOWN

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

UNKNOWN

Open Questions

UNKNOWN

Notes for Future Q&A

May include interpretation. Labeled where it does.

UNKNOWN

Raw Abstract / Excerpt

Background. The widespread deployment of ambient digital scribes is driving large-scale capture of clinician-patient dialogues. Human coding of clinical communication data remains costly, inconsistent, and difficult to scale, motivating AI-driven communication coding systems. However, evaluating these systems requires real-world dialogues and human-coded labels, both hard to obtain at scale. Methods. We developed SIMAX (Scalable and Interpretable Framework for Multi-Fidelity and Annotated Clinician-Patient Dialogue Simulation), a framework for generating controlled clinical dialogue data with reference behavioral annotations. SIMAX generates clinician-patient dialogues from predefined clinical scenarios, personas and voice conditions, and target communication behaviors. Behaviors are controlled using two codebooks: the Global Codebook for overall communication quality and the WISER Codebook for specific countable behaviors. We evaluated SIMAX using automated and human quality assessments and an example communication coding system. Results. SIMAX generated 3,388 simulated dialogues across three specialties, multiple visit stages, persona characteristics, and accent conditions. Automated assessment showed mean UTMOS and WV-MOS scores of 3.03 and 2.61, WER and CER of 0.07 and 0.05, and CLAP cosine similarity of 0.41, suggesting reasonable speech naturalness, high transcription fidelity, and positive text-audio correspondence. Human evaluation showed a median MOS of 4.67 and a median clinical realism score of 3.00. Downstream evaluation suggests that SIMAX can assess how a communication coding system responds to behavioral targets and reveal insufficient sensitivity in some dimensions. Conclusions. SIMAX generates controlled and reproducible simulated clinician-patient dialogues, providing a data foundation for developing, validating, and refining communication coding systems.