fairseq VS stylegan2-pytorch

It might be worth checking out Meta's TTS tho, I haven't gotten the chance to fiddle around with it but it looks somewhat promising https://github.com/facebookresearch/fairseq/tree/main/examples/mms

META's mms supports tts for Persian according to https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html

They have instructions on how to use it in command line and a notebook on how to use it as a python library.

Meta released a new open-source model, Massively Multilingual Speech (MMS) that can do both speech-to-text and text-to-speech in 1,107 languages and can also recognize 4,000+ spoken languages. Existing speech recognition models only cover approximately 100 languages out of the 7,000+ known spoken languages. [Details | Research Paper | GitHub].

Code: https://github.com/facebookresearch/fairseq/tree/main/examples/mms

https://github.com/facebookresearch/fairseq/blob/nllb/LICENS...

The model is CC. Because models aren't software.

export default function ChannelListBottomBar(): JSX.Element { const { client } = useChatContext(); const [micActive, setMicActive] = useState(false); const [audioActive, setAudioActive] = useState(false); return (

{client.user?.image && (

div> )}

{client.user?.name} span> {client.user?.online ? 'Online' : 'Offline'} span> p> button>

setMicActive((currentValue) => !currentValue)} > button> setAudioActive((currentValue) => !currentValue)} > button> button> div> ); }

...then they just use the app on generated images of not real people (potentially based on specific inputs to remind you of a real person).

At lest, a way to complete the AI-generated cycle that https://thispersondoesnotexist.com/ started.

Thispersondoesnotexist.com - It's what the title says. It's terrifying but whenever you refrest the page, it shows you a new "person" who doesn't exist.

This X Does Not Exist is a list of gens for People, Cities, Words, Lyrics and other items that have been created by GANs (generative adversarial networks).

thispersondoesnotexist.com for making profile pics when you want to be anonymous

Nvidia is the one who made GANs popular. All this buzzword that people say about Generative AI, it was popularised by Nvidia with their StyleGAN paper. You must have seen or hear about thispersondoesnotexist.com? That's Nvidia.

GANs on the other hand uses a generator and discriminator model, where the generator learns to generate images that are "good enough" to fool the discriminator. It may make it easier to make discriminators that are better at picking out visual artefacts that stand out for humans, (it was easy to pick out "fake humans" from the early versions of thispersondoesnotexist.com by looking at their eyes and teeth, they tend to be pointing in different directions, or their teeth are too irregular before the discriminator got better at picking those out) but they can suffer from mode collapse, and generate images with very little variety.

Generative networks like StyleGAN