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Maike Züfle

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Preprint Aug 2026

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

KIT's main contribution is a scalable data augmentation pipeline that unifies heterogeneous medical dialogue datasets through synthetic speech generation and automatically generated SOAP supervision, enabling robust adaptation of a speech foundation model for end-to-end speech-to-SOAP generation.

E. Ugan, Fabian Retkowski, Yuka Ko et al. · 0 citations