MEDSAGE: Enhancing Robustness of Medical Dialogue Summarization to ASR Errors with LLM-generated Synthetic Dialogues
Keywords: Information Extraction, Language Generation, Speech Processing, Summarization
TL;DR: The paper proposes using LLMs to generate synthetic ASR-like errors for data augmentation, improving the robustness and accuracy of medical dialogue summarization systems in the low-resource domain of clinical documentation
Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 8th 2024, I specify the DOI in the field below, and I submit the camera-ready version of the paper.
DOI: https://doi.org/ Proceedings are not yet available, here's a the conference programme link: https://aaai.org/wp-content/uploads/2025/02/AAAI-25-Thursday-Poster-Schedule-2.27.25.pdf
Submission Number: 163
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