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drbaph / WavTTS
Model's Last Updated: June 04 2026
text-to-speech
Introduction of WavTTS
Model Details of WavTTS
WavTTS 16k Safetensors for ComfyUI
Safetensors conversion of the official WavTTS model for use with WavTTS-ComfyUI .
This release converts the original PyTorch checkpoint into the Safetensors format for safer loading, improved compatibility with ComfyUI workflows, and reduced storage overhead.
Model Introduction
WavTTS is a zero-shot text-to-speech model that directly generates raw audio waveforms from text using reference-audio prompting.
Unlike token-based TTS systems that generate intermediate acoustic representations, WavTTS models speech directly in the waveform domain, enabling highly natural speech synthesis while preserving speaker characteristics from short reference samples.
Links
- ComfyUI Node: https://github.com/Saganaki22/WavTTS-ComfyUI
- Official Repository: https://github.com/cwx-worst-one/WavTTS
- Research Paper: https://arxiv.org/abs/2606.03455
Usage
This checkpoint is intended for use with:
https://github.com/Saganaki22/WavTTS-ComfyUI
Place the model inside:
ComfyUI/models/wavtts/
Example:
ComfyUI/models/wavtts/
├── wavtts-fp32.safetensors
└── wavtts-mixed-bf16.safetensors
Restart ComfyUI and load the checkpoint using the WavTTS Load Model node.
Model Summary
| Item | Value |
|---|---|
| Model | WavTTS |
| Format | Safetensors |
| Task | Zero-Shot Text-to-Speech |
| Sample Rate | 16 kHz |
| Architecture | Direct Waveform Generation |
| Conditioning | Reference Audio + Reference Transcript |
| Intended Platform | ComfyUI |
| Languages | English, Chinese |
| Training Dataset | Emilia Dataset |
| License | CC BY-NC 4.0 |
Included Variants
| File | Description |
|---|---|
| wavtts-fp32.safetensors | Clean FP32 inference checkpoint |
| wavtts-mixed-bf16.safetensors | Mixed BF16 checkpoint optimized for lower VRAM usage |
The original
.pt
checkpoint contains training-related state that is unnecessary for inference.
Safetensors releases store inference weights only, resulting in smaller file sizes and safer loading behavior.
Intended Use
This model is intended for:
- Zero-shot text-to-speech
- Voice continuation
- Reference-audio conditioned generation
- Voice adaptation from short prompts
- ComfyUI speech workflows
- Local offline TTS generation
A transcript of the reference audio is required by WavTTS.
Precision Notes
FP32
Recommended for maximum stability.
Mixed BF16
Recommended for reduced VRAM usage while preserving numerically sensitive tensors in FP32.
No model weights have been retrained or modified beyond precision conversion.
Architecture
WavTTS performs direct waveform modeling rather than generating intermediate acoustic tokens.
Inputs
- Reference audio
- Reference transcript
- Target text
Output
- 16 kHz synthesized waveform
The model learns speaker characteristics directly from reference audio and generates speech matching the target text in the reference voice style.
Limitations
- Requires a transcript for the reference audio.
- Voice similarity is not guaranteed.
- Long generations may require chunking.
- Audio quality depends heavily on reference quality.
- Commercial usage may be restricted by the upstream license.
- Numerical differences may occur between original and converted checkpoints.
Attribution
Original Authors
WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling
Official repository:
https://github.com/cwx-worst-one/WavTTS
ComfyUI Integration
https://github.com/Saganaki22/WavTTS-ComfyUI
Dataset
https://huggingface.co/datasets/amphion/Emilia-Dataset
License
This Safetensors conversion inherits the licensing terms of the original WavTTS release.
The original model weights are licensed under CC BY-NC 4.0 .
Please review the upstream model card and license terms before redistribution or commercial use.
Citation
@article{chen2026wavtts,
title={WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling},
author={TODO},
journal={TODO},
year={2026}
}
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