SOURCE-LINKED INTELLIGENCE
MedWER: A Reproducible, Model-Free Evaluation Protocol for Medical Speech Recognition
Overall word error rate hides clinically critical errors: a transcript can be 95% correct and still swap one drug for another. The usual fix weights errors on medical entities, and almost always depends on an evaluation-time named-entity recognition (NER) model or cloud API, which makes the metric's denominator a versioned black box. We present MedWER, an evaluation protocol and open-source tool for medical ASR whose denominator is a fixed, license-clean term list: 19,373 drug, diagnosis, symptom, and injury-mechanism entries projected from public sources. The protocol couples a pinned text no
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T21:19:18.000Z
First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.