XTTS-v2_PeterDrury / README.md
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---
license: other
license_name: coqui-public-model-license
license_link: https://coqui.ai/cpml
library_name: coqui
pipeline_tag: text-to-speech
widget:
- text: "Once when I was six years old I saw a magnificent picture"
---
# โ“TTS_v2 - Peter Drury Fine-Tuned Model
This repository hosts a fine-tuned version of the โ“TTS model.
![Peter Drury](peterdrury.jpg)
Listen to a sample of the โ“TTS_v2 - Peter Drury Fine-Tuned Model:
<audio controls>
<source src="https://huggingface.co/kodoqmc/XTTS-v2_PeterDrury/resolve/main/fromtts.wav" type="audio/wav">
Your browser does not support the audio element.
</audio>
Here's a Peter Drury mp3 voice line clip from the training data:
<audio controls>
<source src="https://huggingface.co/kodoqmc/XTTS-v2_PeterDrury/resolve/main/reference.wav" type="audio/wav">
Your browser does not support the audio element.
</audio>
## Features
- ๐ŸŽ™๏ธ **Voice Cloning**: Realistic voice cloning with just a short audio clip.
- ๐ŸŒ **Multi-Lingual Support**: Generates speech in 17 different languages while maintaining Peter Drury's voice.
- ๐Ÿ˜ƒ **Emotion & Style Transfer**: Captures the emotional tone and style of the original voice.
- ๐Ÿ”„ **Cross-Language Cloning**: Maintains the unique voice characteristics across different languages.
- ๐ŸŽง **High-Quality Audio**: Outputs at a 24kHz sampling rate for clear and high-fidelity audio.
## Supported Languages
The model supports the following 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), and Hindi (hi).
## Usage in Roll Cage
๐Ÿค–๐Ÿ’ฌ Boost your AI experience with this Ollama add-on! Enjoy real-time audio ๐ŸŽ™๏ธ and text ๐Ÿ” chats, LaTeX rendering ๐Ÿ“œ, agent automations โš™๏ธ, workflows ๐Ÿ”„, text-to-image ๐Ÿ“โžก๏ธ๐Ÿ–ผ๏ธ, image-to-text ๐Ÿ–ผ๏ธโžก๏ธ๐Ÿ”ค, image-to-video ๐Ÿ–ผ๏ธโžก๏ธ๐ŸŽฅ transformations. Fine-tune text ๐Ÿ“, voice ๐Ÿ—ฃ๏ธ, and image ๐Ÿ–ผ๏ธ gens. Includes Windows macro controls ๐Ÿ–ฅ๏ธ and DuckDuckGo search.
[ollama_agent_roll_cage (OARC)](https://github.com/Leoleojames1/ollama_agent_roll_cage) is a completely local Python & CMD toolset add-on for the Ollama command line interface. The OARC toolset automates the creation of agents, giving the user more control over the likely output. It provides SYSTEM prompt templates for each ./Modelfile, allowing users to design and deploy custom agents quickly. Users can select which local model file is used in agent construction with the desired system prompt.
## CoquiTTS and Resources
- ๐Ÿธ๐Ÿ’ฌ **CoquiTTS**: [Coqui TTS on GitHub](https://github.com/coqui-ai/TTS)
- ๐Ÿ“š **Documentation**: [ReadTheDocs](https://tts.readthedocs.io/en/latest/)
- ๐Ÿ‘ฉโ€๐Ÿ’ป **Questions**: [GitHub Discussions](https://github.com/coqui-ai/TTS/discussions)
- ๐Ÿ—ฏ **Community**: [Discord](https://discord.gg/5eXr5seRrv)
## License
This model is licensed under the [Coqui Public Model License](https://coqui.ai/cpml). Read more about the origin story of CPML [here](https://coqui.ai/blog/tts/cpml).
## Contact
Join our ๐ŸธCommunity on [Discord](https://discord.gg/fBC58unbKE) and follow us on [Twitter](https://twitter.com/coqui_ai). For inquiries, email us at [email protected].
Using ๐ŸธTTS API:
```python
from TTS.api import TTS
tts = TTS(model_path="D:/AI/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_PeterDrury/",
config_path="D:/AI/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_PeterDrury/config.json", progress_bar=False, gpu=True).to(self.device)
# 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 ๐ŸธTTS Command line:
```console
tts --model_name tts_models/multilingual/multi-dataset/xtts_v2 \
--text "Bugรผn okula gitmek istemiyorum." \
--speaker_wav /path/to/target/speaker.wav \
--language_idx tr \
--use_cuda true
```
Using the model directly:
```python
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",
)
```