README.md

---

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"
---


# ⓍTTS_v2 - Peter Drury Fine-Tuned Model



This repository hosts a fine-tuned version of the ⓍTTS model.



![Peter Drury](peterdrury.jpg)



Listen to a sample of the ⓍTTS_v2 - Peter Drury Fine-Tuned Model:

<audio controls>
  <source src="https://huggingface.co./Borcherding/XTTS-v2_C3PO/raw/main/sample_c3po_generated.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./Borcherding/XTTS-v2_C3PO/raw/main/reference2.mp3" type="audio/wav">
  Your browser does not support the audio element.
</audio>

## Features
- 🎙️ **Voice Cloning**: Realistic voice cloning with just a short audio clip.
- 🌍 **Multi-Lingual Support**: Generates speech in 17 different languages while maintaining Peter Drury's voice.
- 😃 **Emotion & Style Transfer**: Captures the emotional tone and style of the original voice.
- 🔄 **Cross-Language Cloning**: Maintains the unique voice characteristics across different languages.
- 🎧 **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
🤖💬 Boost your AI experience with this Ollama add-on! Enjoy real-time audio 🎙️ and text 🔍 chats, LaTeX rendering 📜, agent automations ⚙️, workflows 🔄, text-to-image 📝➡️🖼️, image-to-text 🖼️➡️🔤, image-to-video 🖼️➡️🎥 transformations. Fine-tune text 📝, voice 🗣️, and image 🖼️ gens. Includes Windows macro controls 🖥️ 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
- 🐸💬 **CoquiTTS**: [Coqui TTS on GitHub](https://github.com/coqui-ai/TTS)
- 📚 **Documentation**: [ReadTheDocs](https://tts.readthedocs.io/en/latest/)
- 👩‍💻 **Questions**: [GitHub Discussions](https://github.com/coqui-ai/TTS/discussions)
- 🗯 **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 🐸Community on [Discord](https://discord.gg/fBC58unbKE) and follow us on [Twitter](https://twitter.com/coqui_ai). For inquiries, email us at [email protected].

Using 🐸TTS 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 🐸TTS Command line:

```console

 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:

```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",

)

```