Parler-TTS Mini v0.1

Parler-TTS Mini v0.1 is a lightweight text-to-speech (TTS) model, trained on 10.5K hours of audio data, that can generate high-quality, natural sounding speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation). It is the first release model from the Parler-TTS project, which aims to provide the community with TTS training resources and dataset pre-processing code.

Tips: * Include the term “very clear audio” to generate the highest quality audio, and “very noisy audio” for high levels of background noise * Punctuation can be used to control the prosody of the generations, e.g. use commas to add small breaks in speech * The remaining speech features (gender, speaking rate, pitch and reverberation) can be controlled directly through the prompt

Citation

If you found this repository useful, please consider citing this work and also the original Stability AI paper:

@misc{lacombe-etal-2024-parler-tts,
  author = {Yoach Lacombe and Vaibhav Srivastav and Sanchit Gandhi},
  title = {Parler-TTS},
  year = {2024},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huggingface/parler-tts}}
}

@misc{lyth2024natural,
      title={Natural language guidance of high-fidelity text-to-speech with synthetic annotations},
      author={Dan Lyth and Simon King},
      year={2024},
      eprint={2402.01912},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}