Well first deepfakes need to die. It’s a dangerous tech that should not exist at all and does not need any more research.
To be fair, i haven’t dug into deepfake models, but i assume you would train them on the specific person you’re trying to deepfake: i mean for basic video stuff going with a pre-trained model may be ok but for audio there’s no way you can get away with it ;)
I guess it works fine for very formal speech, where most voices sound alike. But i have strong doubts that it would capture the subtleties of popular/queer speech
Actually the opposite, among the best ones are cartoon characters from TV shows, see https://fakeyou.com/ for example, and that is probably still far from what can be done with a bit more effort.
Well first deepfakes need to die. It’s a dangerous tech that should not exist at all and does not need any more research.
To be fair, i haven’t dug into deepfake models, but i assume you would train them on the specific person you’re trying to deepfake: i mean for basic video stuff going with a pre-trained model may be ok but for audio there’s no way you can get away with it ;)
There are also specific ML models for audio that sound pretty convincing in replicating a specific person’s voice.
I guess it works fine for very formal speech, where most voices sound alike. But i have strong doubts that it would capture the subtleties of popular/queer speech
Actually the opposite, among the best ones are cartoon characters from TV shows, see https://fakeyou.com/ for example, and that is probably still far from what can be done with a bit more effort.
Edit: https://www.wired.co.uk/article/simpsons-deepfake-voice-actors-ai
You’re precisely proving my point that you need a huge sample of voice from that person in order to “replicate” them ;)
EDIT: For example, in the case of Simpsons, they have 25 seasons of voice data to train the model.