chat-tts
Maintainer: thlz998
29
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
chat-tts is an implementation of the ChatTTS model as a Cog model, developed by maintainer thlz998. It is similar to other text-to-speech models like bel-tts, neon-tts, and xtts-v2, which also aim to convert text into human-like speech.
Model inputs and outputs
chat-tts takes in text that it will synthesize into speech. It also allows for adjusting various parameters like voice, temperature, and top-k sampling to control the generated audio output.
Inputs
- text: The text to be synthesized into speech.
- voice: A number that determines the voice tone, with options like 2222, 7869, 6653, 4099, 5099.
- prompt: Sets laughter, pauses, and other audio cues.
- temperature: Adjusts the sampling temperature.
- top_p: Sets the nucleus sampling top-p value.
- top_k: Sets the top-k sampling value.
- skip_refine: Determines whether to skip the text refinement step.
- custom_voice: Allows specifying a seed value for custom voice tone generation.
Outputs
- The generated speech audio based on the provided text and parameters.
Capabilities
chat-tts can generate human-like speech from text, allowing for customization of the voice, tone, and other audio characteristics. It can be useful for applications that require text-to-speech functionality, such as audio books, virtual assistants, or multimedia content.
What can I use it for?
chat-tts could be used in projects that require text-to-speech capabilities, such as:
- Creating audio books or audiobook samples
- Developing virtual assistants or chatbots with voice output
- Generating spoken content for educational materials or podcasts
- Enhancing multimedia presentations or videos with narration
Things to try
With chat-tts, you can experiment with different voice settings, prompts, and sampling parameters to create unique speech outputs. For example, you could try generating speech with different emotional tones or accents by adjusting the voice and prompt inputs. Additionally, you could explore using the custom voice feature to generate more personalized speech outputs.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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