Related Experiment Video
Updated: Jun 7, 2026

A Protocol for Comprehensive Assessment of Bulbar Dysfunction in Amyotrophic Lateral Sclerosis (ALS)
Published on: February 21, 2011
Accent related errors in clinical speech transcription and a LLM-based remedy
Yasaman Fatapour1, Jamil S Samaan2, Nicholas P Tatonetti3,4,5,6
1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Abstract:
Accurate clinical documentation is essential for safe, effective patient care. AI tools powered by automatic speech recognition can streamline this process. Variable performance across speakers with diverse accents leads to transcription errors and clinical risk. In testing Whisper and WhisperX on native and non-native English clinical speech, error rates were significantly higher for non-native speakers. Post-processing with GPT-4o restored lost accuracy. This chained approach (WhisperX-GPT) reduced accent-related errors.
More Related Videos
Related Concept Videos
Improving Translational Accuracy
Master Transcription Regulators
Improving Translational Accuracy
Master Transcription Regulators
Types of Errors: Detection and Minimization
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Larynx
Anatomy of the Larynx
The larynx consists of various components, including cartilage, muscles, and vocal cords. Its structure includes three large unpaired cartilages—the thyroid, cricoid, and epiglottis—and three smaller paired cartilages—the arytenoids, corniculates, and...

