{"paper":{"title":"MedASR: An Open-Source Model for High-Accuracy Medical Dictation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"MedASR is a 105M-parameter open-source model that achieves a 58% relative WER reduction on medical dictation versus Whisper Large-v3.","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Ehsan Variani, Ke Wu, Rory Pilgrim, Shashir Reddy, Tom Bagby","submitted_at":"2026-05-15T18:57:48Z","abstract_excerpt":"We present MedASR, an open-source 105M-parameter model engineered for high-accuracy medical dictation. Prioritizing a \"small, fast, and accurate\" design, MedASR addresses 3 core pillars (1) Data: overcoming clinical corpora scarcity and class imbalance; (2) Modeling: efficient long-form training; and (3) Inference: accurate transcription via a pseudo-streaming sliding-window approach. Our evaluation shows that MedASR achieves a 58% relative WER reduction on Eye Gaze compared to Whisper Large-v3. 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