GitHub Repo: ChatTTS Code from 2noise

Product Characteristics of ChatTTS:

Overview:

• ChatTTS is a conversational speech model tailored for daily dialogues.
• It offers multilingual support, including English and Chinese.
• The model is fine-tuned for dialogue tasks, ensuring natural and expressive speech generation.

Core Objective and Target Audience:

• Core Objective: ChatTTS is crafted for dialogue applications like LLM assistant, specializing in conversational text-to-speech functions.
• Target Audience: Users seeking a text-to-speech model optimized for dialogues, allowing precise control over prosodic elements.

Feature Specifics and Functions:

• Interactive TTS: ChatTTS facilitates interactive dialogues with multi-speaker support.
• Precise Control: Users can anticipate and manage prosodic elements such as laughter, pauses, and interjections.
• Enhanced Prosody: ChatTTS outperforms many open-source TTS models in prosody, offering pretrained models for further exploration.

User Advantages:

• Natural and Expressive Speech Generation: ChatTTS ensures natural and expressive speech output for immersive dialogues.
• Fine-grained Prosodic Control: Users can finely adjust prosodic elements to enhance speech quality.
• Multilingual Support: Trained on Chinese and English audio data, ChatTTS caters to diverse language requirements.

Compatibility and Incorporation:

• ChatTTS is compatible with various platforms and can be seamlessly integrated into diverse text-to-speech applications.
• Integration with Hugging Face enhances ChatTTS with additional functionalities.

Client Testimonials and Use Cases:

• Positive user feedback emphasizes ChatTTS' effectiveness in producing high-quality dialogue speech.
• Use cases showcase ChatTTS' practical applications in enriching user interactions through natural speech synthesis.

Access and Activation Procedure:

• Users can access ChatTTS via the GitHub repository provided by 2noise.
• Activation entails cloning the repository, installing necessary dependencies, and following guidelines for usage and customization.

常见问题

1. ChatTTS 需要多少 VRAM？推理速度如何？

   • 对于 30 秒的音频剪辑，至少需要 4GB 的 GPU 内存。该模型在 4090 GPU 上可以生成大约每秒约 7 个语义标记对应的音频。实时因子（RTF）约为 0.3。

2. 我遇到了模型稳定性问题，比如多说话者问题或音频质量差的情况。有什么建议吗？

   • 这些问题在像 ChatTTS 这样的自回归模型中很常见。完全避免它们可能有挑战性。您可以尝试生成多个样本以找到合适的结果。

3. 除了控制笑声，还有其他可以控制的元素吗？我们可以管理其他情绪吗？

   • 在当前发布的模型中，唯一的令牌级控制单元是 [laugh]、[uv_break] 和 [lbreak]。未来版本可能会包括具有额外情绪控制功能的模型。