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Speech-to-SOAP: End-to-End Summarization of Medical Dialogues: KIT@BeTraC 2026

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within this domain of task the extractive sub-task of clinical protocolling has emerged as a topic of particular interest as it can significantly reduce the downtime and protocolling burden of health-care workers thus enabling them to focus on their core work helping humans. A further step towards automation is the direct generation of clinical notes from speech without intermediate transcripts, reducing processing time while preserving information such as c

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