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Related Experiment Video

Updated: Apr 26, 2026

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
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AI-generated clinical summaries: errors and susceptibility to speech and speaker variability.

Thomas C Draper1, Jason Leake2, Timothy Cox2

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|April 24, 2026
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Summary

Clinical AI Scribe (CAIS) accuracy is stable across patient personalities and most English accents. However, performance degrades with specific speech impairments, particularly phonological impairment, necessitating careful monitoring during deployment.

Keywords:
Artificial intelligenceDelivery of Health CareInformaticsPrimary Health CareSpeech

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Clinical Natural Language Processing

Background:

  • Clinical AI Scribes (CAIS) aim to automate medical documentation.
  • Variability in patient communication (personality, accents, speech impairments) may impact CAIS accuracy.
  • Ensuring CAIS reliability across diverse patient populations is crucial for safe deployment.

Purpose of the Study:

  • To assess the impact of patient communication variability on Clinical AI Scribe (CAIS) accuracy.
  • To identify specific factors (personality, accents, speech impairments) that degrade CAIS performance.
  • To inform validation and monitoring strategies for CAIS pre-deployment.

Main Methods:

  • Simulated primary care consultations using trained actors.
  • Enacted scenarios with diverse patient personality types.
  • Generated accent variations using consultation transcripts and public speech impairment recordings.
  • Classified CAIS errors (omissions, factual inaccuracies, hallucinations) against human transcripts.

Main Results:

  • No statistically significant differences in CAIS errors were found across personality types (p>0.05).
  • CAIS performance was stable across patient and doctor accents, with non-significant differences (p>0.851 for patients, p>0.980 for doctors).
  • Phonological impairment significantly reduced CAIS recognition accuracy (p<0.001), while cleft palate and vowel disorders had minimal impact.

Conclusions:

  • CAIS demonstrates broad stability across communication styles and most accents under controlled conditions.
  • Vulnerability to specific speech characteristics, notably phonological impairment, requires attention.
  • Operational deployment necessitates clinician-in-the-loop verification, subgroup performance monitoring, and 'switch-off' criteria for severe phonological patterns.