MedScribe AI
A clinician-led AI company pioneering ambient clinical documentation, processing hundreds of thousands of clinical encounters weekly across dozens of health systems.
Word Error Rate
Updated 5 min ago via Autoblocks
Overview
Test Description
Measures transcription accuracy by calculating minimum edits needed to match reference text.
Key Metrics
Evaluation
Methodology
Compare AI-generated transcripts against human-written gold standard reference transcripts. Calculate Word Error Rate (WER) as: (number of edits) / (length of reference transcript). Validated through blinded head-to-head trials.
Interpretation of scores
Lower WER indicates better performance. Our model shows a 16% relative reduction in word error rate compared to other medical ASR systems, with a 45% relative reduction in error on new medications.
Dataset
Dataset Description
Over 10,000 hours of clinical conversations with associated audio, gold standard reference transcripts, and rich metadata on patient characteristics. Includes the public Librispeech benchmark dataset and internal medical conversation datasets.