Voice Cloning

Voice cloning is the use of machine learning to build a synthetic model of a specific person's voice, so that new speech can be generated in that voice from written text or from another performer's recorded delivery.^[1] Modern systems rely on deep neural networks that learn a speaker's timbre, rhythm, and pronunciation from reference recordings, then reproduce those traits across new material, and the amount and quality of reference audio strongly affect how faithful the result sounds.

In media production, voice cloning supports dialogue replacement, localization, and the recreation of voices that are otherwise unavailable, including archival material. Because the technology can convincingly imitate real people, it raises legal and ethical questions about consent, likeness rights, and audio deepfakes, which has prompted both industry guidelines and emerging legislation.^[2] Responsible workflows therefore pair the technical process with explicit performer authorization and clear disclosure.^[3]