MedASR: An Open-Source Model for High-Accuracy Medical Dictation

Ke Wu; Ehsan Variani; Tom Bagby; Shashir Reddy; Rory Pilgrim

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arXiv · 2605.16555

MedASR: An Open-Source Model for High-Accuracy Medical Dictation

Ke Wu·Ehsan Variani·Tom Bagby·Shashir Reddy·Rory Pilgrim

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Abstract

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. By open-sourcing MedASR, we provide a transparent, high-performance backbone for specialized health-care applications, breaking down the barriers to clinical documentation often obscured by proprietary systems.

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Ke Wu, Ehsan Variani, Tom Bagby, Shashir Reddy, Rory Pilgrim. 2026-05-15. MedASR: An Open-Source Model for High-Accuracy Medical Dictation. https://arxiv.org/abs/2605.16555

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