Robust Summarization of Doctor-Patient Conversations: TalTech Systems for the Beyond Transcription Challenge
This paper describes TalTech's submissions to the Beyond Transcription Challenge (BeTraC), which requires generating SOAP notes directly from long doctor-patient conversation recordings, without intermediate transcription. After screening open-weight speech LLMs for long-audio robustness, we adapted Voxtral Mini (lightweight track) and Voxtral Small (heavyweight track) with LoRA supervised fine-tuning followed by DAPO reinforcement learning that uses the challenge metric, Open Medical Concept F1, as its reward. Our systems ranked first in both tracks, and an independent LLM-as-a-judge evaluation showed the lowest hallucination rate among all submissions, indicating that reinforcement lear...
| Authors | Aivo Olev, Tanel Alumäe |
|---|---|
| Primary category | cs.CL |
| Published | 19 July 2026 |
| Last updated at source | 19 July 2026 |
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