Replication Data for: Perceived authenticity and acceptance of AI-generated voices in English communication training among health-professions learners and educators: calibrated reproducibility dataset

This dataset contains anonymized participant-level quantitative data supporting a mixed-methods study examining the role of perceived authenticity in the acceptance of AI-generated voices in health-professions English communication training. The dataset includes both wide and long formats, enabling replication of multivariate, signal detection, and mixed-effects analyses. Supporting files include a codebook, README documentation, and an R script for reproducibility. All data are anonymized and structured to reflect the study design and reported analytical relationships. Subject Select: Perceived Authenticity and Acceptance of AI-Generated Voices for English Communication Training in Medical Education: A Mixed-Methods Study Awad Alshehri1 Mohammad Alhammad2 1Imam Mohammad Ibn Saud Islamic University (IMSIU) [e-mail] ORCID https://orcid.org/0000-0002-3937-2413. 2Imam Mohammad Ibn Saud Islamic University (IMSIU) [e-mail] ORCID https://orcid.org/0009-0007-0203-9346 Medicine, Health and Life Sciences Social Sciences Keywords: AI-Generated Speech; Medical Education; English for Medical Purposes (EMP); Human–AI Interaction; Perceived Authenticity; Synthetic Voices; Technology Acceptance. Artificial intelligence Speech synthesis Health professions education Authenticity Mixed methods Signal detection