--- 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 - C-3PO Fine-Tuned Model This repository hosts a fine-tuned version of the โ“TTS model, utilizing 20 unique voice lines from C-3PO, the iconic Star Wars character. The voice lines were sourced from [Voicy](https://www.voicy.network/official-soundboards/movies/c3po). ![C-3PO](c3po_1.png) Listen to a sample of the โ“TTS_v2 - C-3PO Fine-Tuned Model: Here's a C-3PO mp3 voice line clip from the training data: ## 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 C-3PO's distinct 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. ## Why This Model for Roll Cage? 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. ## 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 info@coqui.ai. Using ๐ŸธTTS API: ```python from TTS.api import TTS tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True) # 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", ) ```