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ChatTTS is a specialized text-to-speech (TTS) model built for conversational applications like virtual assistants and chatbots. It converts text into natural, expressive speech in both English and Chinese. Trained on massive datasets—100,000 hours for the full version and 40,000 hours for the open-source version—it provides precise control over prosodic elements, including laughter, pauses, and interjections.
To use ChatTTS, enter your text into the interface. You can then refine the input and adjust settings such as audio temperature, top_P, top_K, audio seed, and text seed to customize the generated audio output.
You need at least 4GB of GPU memory to process a 30-second audio clip. On a 4090 GPU, the model generates audio at approximately 7 semantic tokens per second, achieving a Real-Time Factor (RTF) of about 0.3.
These challenges are common in autoregressive models such as Bark and Valle. While it can be difficult to manage, generating multiple samples often helps in finding a high-quality result.
At present, the only available token-level controls are [laugh], [uv_break], and [lbreak]. Future updates may introduce additional emotional control features.
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