AI voice generation has just made a massive leap ahead 15.ai, now on par with GPT-3 text generation and Stable Diffusion image generation. This is the next wave of machine learning magic and it's hitting the coast with tsunami force. >What the fuck does this have to do with videogames? Using clips from your favorite videogame voices you can make those voices say anything you want, just like 15.ai could, but with immensely greater quality. No more grainy, scratchy earrape. It even generates a proper accent if your feed it something that isn't English. You can use it to mod your dialogue into the game, or to make dialogue for your own game. Also, you can make anyone you want say NIGGER all day. The possibilities are endless. https://beta.elevenlabs.io/ Get the fuck in here and make a free account with a disposable email to generate up to roughly 10 minutes of dialogue a month with up to five storable voices at a time. Use more emails for more accounts for more free dialogue. 10 minute email works. No one can predict if these fags will jack prices or cuck out like DungeonAI, and people may not be so lucky as get viable alternatives right after they cuck out. The time to act is now.

Jointly operating with 4chan frens: We want to fork this text to speech synthesis project to compete with 11labs speech synthesizer. Source code for tortoise tts https://github.com/neonbjb/tortoise-tts here is the specific code we need to break down and understand https://github.com/neonbjb/tortoise-tts/blob/main/tortoise/utils/diffusion.py training models used https://github.com/neonbjb/tortoise-tts/tree/main/tortoise/models Source for the trainer project tortoise used https://github.com/neonbjb/DL-Art-School Tortoise tts videos https://www.youtube.com/watch?v=J3-jfS29RF4 https://www.youtube.com/watch?v=Kfr_FZof_hs https://www.youtube.com/watch?v=FN3yxL0Rr0c we have datasets https://github.com/LAION-AI/audio-dataset Given the potentially large datasets involved it is a prudent strategy to decentralize training going forward. If you know anything about federated training or understand about these github projects can you explain which are the best and most relevant.

Copied from previous OP. Here's some guides to installing Stable Diffusion (if you have a NVIDIA GPU with 2GB+ VRAM). >Installing AUTOMATIC1111, the most feature-rich and commonly-used UI: https://rentry.org/voldy >Different UI with 1-click installation: https://github.com/cmdr2/stable-diffusion-ui >Installing various UIs in Docker: https://github.com/AbdBarho/stable-diffusion-webui-docker >AMD isn't well-supported. If you're running Linux there's a way to install AUTOMATIC1111 but otherwise features are very limited: Native: https://rentry.org/sd-nativeisekaitoo Docker: Copied from previous OP. Here's some guides to installing Stable Diffusion (if you have a NVIDIA GPU with 2GB+ VRAM). >Installing AUTOMATIC1111, the most feature-rich and commonly-used UI: https://rentry.org/voldy >Different UI with 1-click installation: https://github.com/cmdr2/stable-diffusion-ui >Installing various UIs in Docker: https://github.com/AbdBarho/stable-diffusion-webui-docker >AMD isn't well-supported. If you're running Linux there's a way to install AUTOMATIC1111 but otherwise features are very limited: Native: https://rentry.org/sd-nativeisekaitoo