We developed custom voice‑cloning pipelines that can generate convincing synthetic voices with only a short sample of a target speaker. Voice‑cloning technology uses deep generative models to learn the timbre, accent and intonation patterns of a speaker, then synthesize new audio in that voice. Research on AI‑generated voices shows that listeners sometimes find voice clones indistinguishable from real voices. Our workflow involved curating clean audio samples, training and fine‑tuning synthesis models, and building a simple interface for generating speech in the cloned voice.
Outcome: The resulting voice clones deliver natural‑sounding speech that captures the speaker’s identity and prosody. The technology has applications in accessibility (e.g., reading devices for visually impaired users) and personalized digital assistants. We also explored ethical safeguards to prevent misuse, since realistic voice clones can also mislead audiences.
Voice Cloning
Custom pipelines that synthesize natural-sounding speech from brief audio samples. Captures timbre, accent, and intonation with built-in ethical safeguards.