Accepted for/Published in: JMIR Medical Education
Date Submitted: Oct 27, 2025
Date Accepted: May 19, 2026
Voice-cloning using artificial intelligence versus traditional audio recording for pre-recorded courses in medical pedagogy: a randomized controlled trial
ABSTRACT
Background:
Pre-recorded courses are increasingly used in medical education, and audio quality is known to influence learners’ comprehension and engagement. Traditional audio recording, however, is time-consuming and may be uncomfortable for some educators. Advances in generative artificial intelligence (AI) now allow realistic voice cloning, but its pedagogical value compared with conventional recording has not been assessed.
Objective:
To evaluate the usefulness and perception of AI-based voice cloning for pre-recorded courses in medical pedagogy compared with traditional audio recording.
Methods:
We conducted a randomized trial among fourth- and fifth-year medical students at a French university. Participants accessed four 10-minutes pre-recorded lectures on critical appraisal of medical research. The control group received lectures with audio recorded by the teacher, while the intervention group received audio generated from the teacher’s cloned voice using a commercial AI text-to-speech system, with identical slides and scripts. Primary outcome was the total score on two online tests (knowledge acquisition, 17 MCQs; knowledge application, 15 MCQs). Secondary outcomes included satisfaction ratings, course viewing metrics, and production time.
Results:
Eighty-eight students were randomized, and 64 watched at least 15 seconds of video and were thus included in the modified intention-to-treat population. Mean total test scores did not differ significantly between AI voice cloning and audio recording groups (51.2 vs. 51.8/100; adjusted mean difference −0.9 [95% CI, -2.7, +4.4], p=0.60). Satisfaction was high in both groups, with no significant differences across items. Production time was shorter with AI (22.5 vs. 35 minutes per video).
Conclusions:
AI voice cloning produced learning and satisfaction outcomes comparable to conventional recording while reducing preparation time, making it a practical alternative for pre-recorded medical courses. Nevertheless, some students may perceive synthetic voices as less authentic, representing a potential barrier to widespread adoption.
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