Listen to a sample of the ⓍTTS_v2 - Peter Drury Fine-Tuned Model:
Here's a Peter Drury mp3 voice line clip from the training data:
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) 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.
1from TTS.api import TTS
23tts = TTS(model_path="D:/AI/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_PeterDrury/",4 config_path="D:/AI/ollama_agent_roll_cage/AgentFiles/Ignored_TTS/XTTS-v2_PeterDrury/config.json", progress_bar=False, gpu=True).to(self.device)56# generate speech by cloning a voice using default settings7tts.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.",8 file_path="output.wav",9 speaker_wav="/path/to/target/speaker.wav",10 language="en")11
1from TTS.tts.configs.xtts_config import XttsConfig
2from TTS.tts.models.xtts import Xtts
34config = XttsConfig()5config.load_json("/path/to/xtts/config.json")6model = Xtts.init_from_config(config)7model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/",eval=True)8model.cuda()910outputs = model.synthesize(11"It took me quite a long time to develop a voice and now that I have it I am not going to be silent.",12 config,13 speaker_wav="/data/TTS-public/_refclips/3.wav",14 gpt_cond_len=3,15 language="en",16)
