tts-hub/XTTS-v2

XTTS

XTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip. There is no need for an excessive amount of training data that spans countless hours.

Paper: https://arxiv.org/abs/2406.04904

Features

• Supports 17 languages.
• Voice cloning with just a 6-second audio clip.
• Emotion and style transfer by cloning.
• Cross-language voice cloning.
• Multi-lingual speech generation.
• 24khz sampling rate.

Updates over XTTS-v1

• 2 new languages; Hungarian and Korean
• Architectural improvements for speaker conditioning.
• Enables the use of multiple speaker references and interpolation between speakers.
• Stability improvements.
• Better prosody and audio quality across the board.

Languages

XTTS-v2 supports 17 languages: English (en), Spanish (es), French (fr), German (de), Italian (it), Portuguese (pt), Polish (pl), Turkish (tr), Russian (ru), Dutch (nl), Czech (cs), Arabic (ar), Chinese (zh-cn), Japanese (ja), Hungarian (hu), Korean (ko) Hindi (hi).

Code

The code-base supports inference and fine-tuning.

🐸💬 CoquiTTS	GitHub
💼 Documentation	ReadTheDocs
👩‍💻 Questions	GitHub Discussions
🗯 Community	Discord

License

This model is licensed under Coqui Public Model License. There's a lot that goes into a license for generative models, and you can read more of the origin story of CPML here.

Contact

Come and join in our 🐸Community, we're active on Discord.

Using 🐸TTS API:

from TTS.api import TTS
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to("cuda")

# Generate speech by cloning a voice using default settings
tts.tts_to_file(
  text="It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.",
  file_path="output.wav",
  speaker_wav="/path/to/target/speaker.wav",
  language="en"
)

Using 🐸TTS Command line:

tts --model_name tts_models/multilingual/multi-dataset/xtts_v2 \
    --text "Bugün okula gitmek istemiyorum." \
    --speaker_wav /path/to/target/speaker.wav \
    --language_idx tr \
    --use_cuda true

Using the model directly:

from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.models.xtts import Xtts

config = XttsConfig()
config.load_json("/path/to/xtts/config.json")
model = Xtts.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/", eval=True)
model.cuda()

outputs = model.synthesize(
    "It took me quite a long time to develop a voice and now that I have it I am not going to be silent.",
    config,
    speaker_wav="/data/TTS-public/_refclips/3.wav",
    gpt_cond_len=3,
    language="en",
)