XTTS V2 C3PO

🚀 ⓍTTS_v2 - C-3PO Fine-Tuned Voice Model (Borcherding/XTTS-v2_C3PO)

The ⓍTTS (Satirical Text-to-Speech) model in the Borcherding/XTTS-v2_C3PO repository is not just a technological tool. It's an art piece, combining code, creativity, and humor. Picture a digital gallery where C-3PO's satirical musings echo through virtual halls.

🚀 Quick Start

You can use this fine - tuned ⓍTTS model in multiple ways:

Using 🐸TTS API

from TTS.api import TTS

tts = TTS(model_path="D:/CodingGit_StorageHDD/Ollama_Custom_Mods/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_C3PO/", 
          config_path="D:/CodingGit_StorageHDD/Ollama_Custom_Mods/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_C3PO/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

 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",
)

✨ Features

• 🎙️ Voice Cloning: Realistic voice cloning with just a short audio clip.
• 🌍 Multi - Lingual Support: Generates speech in 17 different languages while maintaining C - 3PO's distinct 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.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

Basic Usage

You can use the provided code examples above to generate speech. For example, using the 🐸TTS API:

from TTS.api import TTS

tts = TTS(model_path="D:/CodingGit_StorageHDD/Ollama_Custom_Mods/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_C3PO/", 
          config_path="D:/CodingGit_StorageHDD/Ollama_Custom_Mods/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_C3PO/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")

Advanced Usage

Using the model directly provides more control over the synthesis process:

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",
)

📚 Documentation

• 🐸💬 idiap/CoquiTTS: Coqui TTS on GitHub
• 👩‍💻 daswer123/xtts-finetune-webui 👩‍💻: xtts-finetune-webui
• 📚 Documentation: ReadTheDocs
• 👩‍💻 Questions: GitHub Discussions
• 🗯 Community: Discord

🔧 Technical Details

The ⓍTTS model uses 20 unique voice lines sourced from Voicy to capture C - 3PO's distinctive speech patterns. It has a satirical tone, playfully exaggerating intonation, injecting humorous pauses, and occasionally breaking the fourth wall.

📄 License

This model is licensed under the Coqui Public Model License. Read more about the origin story of CPML here.

Contact

Join our 🐸Community on Discord and follow us on Twitter. For inquiries, email us at info@coqui.ai.

You can listen to a sample of the ⓍTTS_v2 - C - 3PO Fine - Tuned Model:

Here's a C - 3PO mp3 voice line clip from the training data:

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).

ollama_agent_roll_cage (OARC) 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.

The C - 3PO fine - tuned model was designed for the Roll Cage chatbot to enhance user interaction with a familiar and beloved voice. By incorporating C - 3PO's distinctive speech patterns and tone, Roll Cage becomes more engaging and entertaining. The addition of multi - lingual support and emotion transfer ensures that the chatbot can communicate effectively and expressively across different languages and contexts, providing a more immersive experience for users.