Deep learning models for natural voice cloning methods were first developed in 2016, and since then, the researchers'
main attention has been on making the voice more realistic and obtaining the output voice in real-time. Previously it used to take
many hours of voice samples to clone a few seconds. It was decreased to a few seconds after utilizing deep learning models. We
shall look at various voice cloning techniques in this paper. Multi-speaker generative models, speaker adoption, speaker
encoding, vector quantization, and other techniques are among them.
