aceA Controlled Single-Speaker Evaluation of Ambient Voice Technologies' Speech-to-Text Function Using Narrated Surgical Case-Reports
Ambient voice technologies (AVT) utilise automatic speech recognition (ASR) and generative artificial intelligence for speech-to-text conversion, and are advocated as efficient, accurate tools for clinical documentation. We investigated (n = 8) AVT systems using surgical case-reports as narratives in a controlled single-speaker evaluation prioritising safety outcomes: specifically 3 commercial transcription-systems (Dragon-Medical-One, Heidi-Health, Tortus); 4 ASR speech-to-text Application Programming Interface…
Adding GPT-5 generative error correction to a GPT4oTranscribe pipeline reduced the share of transcripts with clinically significant Class 3 errors from 53% to 30%, resolving 51 of 89 such errors.
Every tested ambient voice system produced clinically significant Class 3 errors in 30-68% of transcripts, including 53 errors with potential for severe harm or death, mostly in medication and laboratory result details.
The evaluation used a single speaker and narratives derived from surgical case reports in a controlled setting, and the authors state that safety and effectiveness in clinical practice require further evaluation.
Evidence
- Peer-reviewedJournal of Medical Systems2026-10-09
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Truvace Impact Record TRV-2026-1687, v1: “A Controlled Single-Speaker Evaluation of Ambient Voice Technologies' Speech-to-Text Function Using Narrated Surgical Case-Reports.” Truvace, 2026-10-17. /record/TRV-2026-1687 (accessed at citation time). sha256 57106dd0b8eff6fd…
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