Extensions/ComfyUI-FL-Qwen3TTS
ComfyUI Extension

ComfyUI-FL-Qwen3TTS

Qwen3-TTS text-to-speech nodes for ComfyUI with voice cloning, voice design, and fine-tuning UI

By filliptm·Created 7 months ago·Updated 2 days ago· 149
filliptm/ComfyUI-FL-Qwen3TTS
Nodes10
On cloudLocal install
CategoryFL/Qwen3TTS, FL/Qwen3TTS/Training
Stars149
Updated2 days ago
Readme

FL Qwen3 TTS

Advanced text-to-speech nodes for ComfyUI powered by Alibaba's Qwen3-TTS model family. Features voice cloning, voice design from text descriptions, predefined speakers, and a built-in fine-tuning UI with real-time training dashboard.

Qwen3-TTS Patreon

Workflow Preview

Features

  • Voice Cloning - Clone any voice from 5-15 seconds of reference audio
  • Voice Design - Create custom voices from natural language descriptions
  • 9 Predefined Speakers - Ready-to-use voices across Chinese, English, Japanese, and Korean
  • Fine-Tuning UI - Train custom voice models with a real-time dashboard (loss chart, progress, validation audio)
  • 10 Languages - Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian
  • Auto Transcription - Built-in Whisper integration for generating reference text
  • Audio Codec - Encode and decode audio using the Qwen3-TTS 12Hz tokenizer

Nodes

| Node | Description | |------|-------------| | Model Loader | Downloads and caches Qwen3-TTS models from HuggingFace | | Tokenizer Loader | Loads the 12Hz audio tokenizer for encoding/decoding | | Custom Voice | Generate speech using 9 predefined speakers with optional style instructions | | Voice Design | Create voices from natural language descriptions (e.g. "a warm British female voice") | | Voice Clone | Clone a voice from reference audio | | Voice Clone Prompt | Pre-compute a voice prompt for efficient multi-generation cloning | | Audio Encode | Encode audio to discrete codes using the tokenizer | | Audio Decode | Decode discrete codes back to audio | | Transcribe | Transcribe audio to text using Whisper (useful for ref_text) | | Training UI | All-in-one fine-tuning with real-time training dashboard |

Installation

ComfyUI Manager

Search for "FL Qwen3 TTS" and install.

Manual

cd ComfyUI/custom_nodes
git clone https://github.com/filliptm/ComfyUI-FL-Qwen3TTS.git
cd ComfyUI-FL-Qwen3TTS
pip install -r requirements.txt

Quick Start

Text-to-Speech

  1. Add FL Qwen3 TTS Model Loader and select a model variant
  2. Connect to Custom Voice, Voice Design, or Voice Clone node
  3. Enter your text, configure voice settings, and generate

Voice Cloning

  1. Load the Base model (Qwen3-TTS-12Hz-1.7B-Base)
  2. Connect to Voice Clone with 5-15 seconds of reference audio
  3. Optionally use Transcribe to generate ref_text for better results
  4. Enter target text and generate

Fine-Tuning

  1. Prepare a folder with audio files and matching .txt transcripts
  2. Add the Training UI node and point it to your dataset folder
  3. Configure training parameters (learning rate, epochs, etc.)
  4. Run the workflow — monitor progress in the real-time dashboard
  5. Use the output checkpoint with Custom Voice for inference

Models

| Model | Type | Use Case | |-------|------|----------| | Qwen3-TTS-12Hz-1.7B-Base | Base | Voice cloning and fine-tuning | | Qwen3-TTS-12Hz-1.7B-CustomVoice | Custom Voice | 9 predefined speakers with style control | | Qwen3-TTS-12Hz-1.7B-VoiceDesign | Voice Design | Create voices from text descriptions |

Models download automatically on first use to ComfyUI/models/tts/Qwen3TTS/.

Predefined Speakers

Available with the CustomVoice model:

| Speaker | Language | Description | |---------|----------|-------------| | Vivian | Chinese | Bright, edgy female | | Serena | Chinese | Warm, gentle female | | Uncle_Fu | Chinese | Seasoned male | | Dylan | Chinese | Beijing dialect male | | Eric | Chinese | Sichuan dialect male | | Ryan | English | Dynamic male | | Aiden | English | American male | | Ono_Anna | Japanese | Japanese female | | Sohee | Korean | Korean female |

Dataset Format (Training)

audio_folder/
  sample1.wav
  sample1.txt    # contains transcript of sample1.wav
  sample2.mp3
  sample2.txt
  ...

Supported audio formats: .wav, .mp3, .flac, .ogg, .m4a

Requirements

  • Python 3.9+
  • 16GB RAM minimum (32GB+ recommended for training)
  • NVIDIA GPU with 12GB+ VRAM recommended (CPU and Mac MPS supported for inference)

License

Apache 2.0