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Chatterbox AI
Overview :
Chatterbox is the first open-source production-grade text-to-speech (TTS) model released by Resemble AI, featuring outstanding performance and stability. It shows superior results compared to top closed-source systems. The unique aspect of this model is its support for exaggerated emotional control, making it ideal for use in video games, AI agents, and various other scenarios. Chatterbox offers strong price competitiveness and supports super-low latency, making it suitable for production use.
Target Users :
This product is suitable for content creators, game developers, and AI application developers, helping them quickly generate high-quality voice content, enhancing the expressiveness and appeal of their works.
Use Cases
Creating voice dialogues for game characters.
Adding emotional narration to videos.
Building AI assistants with personalized voices.
Features
Advanced zero-shot TTS technology, enabling natural voice generation based on different inputs.
0.5B Llama backbone ensures high-quality voice synthesis.
Emotional exaggeration and intensity control make the sound more vivid.
Stable alignment reasoning ensures smoothness of generated speech.
Trained on 500k hours of cleaned data with superior audio quality.
Built-in watermark function ensures responsibility of generated content.
Simple voice conversion scripts make personalized voice synthesis convenient.
How to Use
Install dependencies: Use the command pip install chatterbox-tts to install the Chatterbox library.
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Import required libraries: Import the torchaudio and ChatterboxTTS modules in Python code.
Load the model: Load the model using the ChatterboxTTS.from_pretrained() method, specifying the device as 'cuda'.
Generate speech: Call the model.generate() method, passing in the text to be synthesized to generate audio data.
Save audio: Use the save method from torchaudio to save the generated audio data as a .wav file.
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