Abstract: The systems and methods disclosed herein generate a personalized inner voice audio output that replicates or otherwise shares the acoustic characteristics of a speaker's self-perceived voice, which can differ from their externally perceived voice due to bone conduction effects. The systems and methods disclosed herein can generate a provisional voice clone (e.g., parameters of a voice model) of the speaker's voice (e.g., using a recording of the speaker's voice), and can apply a frequency shift to compensate for the absence of bone-conducted low-frequency adjustment that occurs during natural speech production. A trained artificial intelligence model predicts and applies one or more additional acoustic parameter adjustment values (e.g., formant structure, spectral envelope, prosodic patterns) to the provisional voice clone based on one or more factors (e.g., demographic, anatomical, content, environment). The provisional voice clone can be iteratively refined based on received user feedback (e.g.