Voice cloning

Synthesize a digital, hyper-realistic copy of a person's voice, including accent and emotion, using deep learning algorithms on minimal audio data.

Voice cloning leverages end-to-end deep neural networks (like Tacotron and WaveNet) to analyze a speaker's unique vocal fingerprint: pitch, tone, and prosody. This generative AI process requires as little as 30 seconds of audio to create a high-fidelity, text-to-speech model, producing new content with over 95% similarity to the original source. Key applications include media localization, entertainment (posthumous voice use), and accessibility (voice restoration for patients), but the technology's high realism also introduces significant fraud and security risks, prompting regulatory action from bodies like the FTC.

https://www.ftc.gov/business-guidance/blog/2024/04/approaches-address-ai-enabled-voice-cloning