Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization

The paper introduces a synthetic data generation pipeline for long‑context audio reasoning, focusing on first‑visit doctor‑patient conversations and SOAP note generation. The pipeline consists of persona‑driven dialogue creation, multi‑speaker audio synthesis with realistic acoustics, and LLM‑based reference note production, all built with open‑weight models. The authors release 8,800 synthetic conversations, 1.3k hours of audio, and reference notes, and show that cascaded approaches still outperform end‑to‑end models on current open‑weight systems.

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• llms
• nlp
• benchmarks