xtts-v2

Maintainer: lucataco

Total Score

313

Last updated 9/18/2024
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Paper linkView on Arxiv

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Model overview

The xtts-v2 model is a multilingual text-to-speech voice cloning system developed by lucataco, the maintainer of this Cog implementation. This model is part of the Coqui TTS project, an open-source text-to-speech library. The xtts-v2 model is similar to other text-to-speech models like whisperspeech-small, styletts2, and qwen1.5-110b, which also generate speech from text.

Model inputs and outputs

The xtts-v2 model takes three main inputs: text to synthesize, a speaker audio file, and the output language. It then produces a synthesized audio file of the input text spoken in the voice of the provided speaker.

Inputs

  • Text: The text to be synthesized
  • Speaker: The original speaker audio file (wav, mp3, m4a, ogg, or flv)
  • Language: The output language for the synthesized speech

Outputs

  • Output: The synthesized audio file

Capabilities

The xtts-v2 model can generate high-quality multilingual text-to-speech audio by cloning the voice of a provided speaker. This can be useful for a variety of applications, such as creating personalized audio content, improving accessibility, or enhancing virtual assistants.

What can I use it for?

The xtts-v2 model can be used to create personalized audio content, such as audiobooks, podcasts, or video narrations. It could also be used to improve accessibility by generating audio versions of written content for users with visual impairments or other disabilities. Additionally, the model could be integrated into virtual assistants or chatbots to provide a more natural, human-like voice interface.

Things to try

One interesting thing to try with the xtts-v2 model is to experiment with different speaker audio files to see how the synthesized voice changes. You could also try using the model to generate audio in various languages and compare the results. Additionally, you could explore ways to integrate the model into your own applications or projects to enhance the user experience.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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