Table 2_The tongue may not move, but the voice will: preoperative AI voice cloning for identity preservation in major glossectomy — a prospective feasibility study.xlsx

Subjective acceptance was assessed using the Personalised Synthetic Voice Acceptance Questionnaire across six domains, completed by patients and family members.</p>Results<p>Of 34 enrolled patients, 26 formed the final cohort across four languages. Mean cosine similarity was 0.933 (Resemblyzer), 0.969 (WavLM), and 0.806 (ECAPA-TDNN), with clone scores generally falling within patient-specific intra-speaker distributions and above cohort impostor distributions.

Mean mel-cepstral distortion was 7.87 dB. Fundamental frequency and other prosodic measures showed broad cohort-level correspondence with variable individual deviations. Identity-and-Ownership and Authenticity-and-Trust domains scored highest among both patients and family or attenders, while naturalness and emotional acceptance were rated more conservatively.</p>Conclusion<p>These findings demonstrate the feasibility of generating personalised synthetic voices from brief preoperative clinic-grade recordings, with objective speaker similarity and preliminary patient- and family-reported acceptance.

The findings support further evaluation of these voices as potential assistive communication tools during postoperative recovery; however, postoperative communication performance and clinical benefit were not evaluated in the present study.</p>