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DreamVoice: Text-guided Voice Conversion

Introduction

DreamVoice is an innovative approach to voice conversion (VC) that leverages text-guided generation to create personalized and versatile voice experiences. Unlike traditional VC methods, which require a target recording during inference, DreamVoice introduces a more intuitive solution by allowing users to specify desired voice timbres through text prompts.

For more details, please check our interspeech paper: DreamVoice

Demo

🎵 Listen to examples

Installation

Make sure you have git-lfs installed:

git lfs install

Clone the repository and install the dependencies:

git clone [email protected]:myshell-ai/DreamVoice.git
cd DreamVoice
pip install -r requirements.txt

Gradio Demo

python gradio_demo.py

API Usage

You can use the model with the following code:

  • End-to-end mode (DreamVC)
from dreamvoice import DreamVoice

# Initialize DreamVoice in end-to-end mode with CUDA device
dreamvoice = DreamVoice(mode='end2end', device='cuda')
# Provide the path to the content audio and generate the converted audio
gen_end2end, sr = dreamvoice.genvc('examples/test1.wav', prompt)
# Save the converted audio
dreamvoice.save_audio('gen_end2end.wav', gen_end2end, sr)

# Note: End-to-end mode does not support saving speaker embeddings
# To use a voice generated in end-to-end mode, switch back to plugin mode
# and extract the speaker embedding from the generated audio
# Switch back to plugin mode
dreamvoice = DreamVoice(mode='plugin', device='cuda')
# Load the speaker audio from the previously generated file
gen_end2end2, sr = dreamvoice.simplevc('examples/test2.wav', speaker_audio='gen_end2end.wav')
# Save the new converted audio
dreamvoice.save_audio('gen_end2end2.wav', gen_end2end2, sr)
  • Plugin mode (DreamVG + DiffVC)
from dreamvoice import DreamVoice

# Initialize DreamVoice in plugin mode with CUDA device
dreamvoice = DreamVoice(mode='plugin', device='cuda')
# Description of the target voice
prompt = 'young female voice, sounds young and cute'
# Provide the path to the content audio and generate the converted audio
gen_audio, sr = dreamvoice.genvc('examples/test1.wav', prompt)
# Save the converted audio
dreamvoice.save_audio('gen1.wav', gen_audio, sr)

# Save the speaker embedding if you like the generated voice
dreamvoice.save_spk_embed('voice_stash1.pt')
# Load the saved speaker embedding
dreamvoice.load_spk_embed('voice_stash1.pt')
# Use the saved speaker embedding for another audio sample
gen_audio2, sr = dreamvoice.simplevc('examples/test2.wav', use_spk_cache=True)
dreamvoice.save_audio('gen2.wav', gen_audio2, sr)
  • One-shot Voice Conversion (DiffVC)
from dreamvoice import DreamVoice

# Plugin mode can be used for traditional one-shot voice conversion
dreamvoice = DreamVoice(mode='plugin', device='cuda')
# Generate audio using traditional one-shot voice conversion
gen_tradition, sr = dreamvoice.simplevc('examples/test1.wav', speaker_audio='examples/speaker.wav')
# Save the converted audio
dreamvoice.save_audio('gen_tradition.wav', gen_tradition, sr)

Reference

If you find the code useful for your research, please consider citing:

@article{hai2024dreamvoice,
  title={DreamVoice: Text-Guided Voice Conversion},
  author={Hai, Jiarui and Thakkar, Karan and Wang, Helin and Qin, Zengyi and Elhilali, Mounya},
  journal={arXiv preprint arXiv:2406.16314},
  year={2024}
}