F5-TTS-THAI
| Property | Value |
|---|---|
| Base Model | SWivid/F5-TTS |
| Training Steps | 430,000 |
| Dataset Size | 90,000 samples (~100 hours) |
| GitHub Repository | VYNCX/F5-TTS-THAI |
What is F5-TTS-THAI?
F5-TTS-THAI is a specialized text-to-speech model designed specifically for the Thai language. Built upon the SWivid/F5-TTS architecture, this model has been extensively trained on Porameht's processed voice dataset containing 90,000 Thai voice samples, equivalent to approximately 100 hours of speech data.
Implementation Details
The model has undergone 430,000 training steps and requires CUDA-compatible GPU support for optimal performance. It's implemented with PyTorch 2.3.0 and includes a user-friendly web interface for easy interaction.
- Built on the F5-TTS architecture
- Trained on high-quality Thai speech dataset
- Includes web-based interface (f5_tts_webui.py)
- CUDA-optimized for GPU acceleration
Core Capabilities
- Thai text-to-speech synthesis
- Support for extended text passages
- Customizable speech generation through seed values
- Web-based interface for easy usage
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for Thai language speech synthesis, trained on a substantial dataset of 90,000 voice samples. It provides a practical solution for Thai TTS applications while leveraging the robust F5-TTS architecture.
Q: What are the recommended use cases?
The model is suitable for Thai language text-to-speech applications, though it's noted that performance may vary with longer text passages or certain words. It's ideal for basic to moderate complexity Thai text conversion tasks where natural-sounding speech is required.
