Peter Griffin (BeefFishStick)
RVC v2EnglishFictionalE-celeb

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From the creator

"Yes audio is messed up. Sadly I couldn't find most of the audios on HQ also I had to search in the hiddest places on internet to find more material from this guy doing the Peter Griffin meme voice impression. I found 15 minutes of audio but the quality from most of them is different (some of them are in HQ others not) and I believe that it involves in some part with the model's quality audio but well it was the best I could do about this. (For those who don't get this voice is the Peter Griffin from the "Holy Crap i'm in fortnite meme" or "Holy f Lois i'm coming")"

Description

Introducing our latest advanced AI voice model, named "Peter Griffin (BeefFishStick), RMVPE, RVC V2, 200 Epochs." This state-of-the-art model utilizes Retrieval-Based Voice Conversion (RVC) technology, version two, to generate highly realistic and engaging audio output. With its impressive 200 epochs of training, this model specializes in creating authentic renditions of Peter Griffin's iconic voice from the popular animated series Family Guy, under the persona BeefFishStick. Our RVC Model leverages cutting-edge artificial intelligence techniques to deliver remarkable text-to-speech capabilities, generating humanlike speech patterns effortlessly. Moreover, it provides unique opportunities for users looking to create AI covers or incorporate synthetic voices into their projects โ€“ opening doors for creators working within music production, podcasting, and other multimedia formats. Unlock new creative possibilities by exploring the world of AI music generation through our powerful suite of free tools at Weights! Whether you want to produce your very own AI covers or enhance storytelling experiences with top-notch text-to-speech features, look no

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Comments

Audio removed in response to copyright claim.

Audio removed in response to copyright claim.

I made an audio of my voice to try to simulate how this Peter Griffin sounds and converted it with the AI model

Audio removed in response to copyright claim.

theres a lot of artifacting with this model. you mentioned you had around 15 minutes of audio for the dataset and some were hq and some werent. the parts that arent hq are most likely the issue with this model. It might come out significantly better if you keep solely the hq data even if theres less data to train on.

this is amazing

My intention was to make the model sound like that to remember the memes. But yeah thanks for the advice anyways

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