Qwen3-TTS Studio

A professional-grade interface for Qwen3-TTS, designed to unlock the model's full potential with fine-grained control and intuitive workflows.

Why This Project?

Qwen3-TTS is a powerful text-to-speech model, but using it directly requires dealing with complex parameters, manual prompt engineering, and repetitive boilerplate code. Qwen3-TTS Studio was created to solve these problems:

• Fine-tuned Control: Easily adjust temperature, top-k, top-p, and other parameters with real-time presets (Fast / Balanced / Quality)
• Better Results: Optimized default settings and automatic token management to avoid common issues like silent audio or distorted output
• Intuitive UI/UX: Clean, modern interface that makes voice generation accessible to everyone
• Automated Podcasts: Generate complete podcasts from just a topic - AI writes the script, assigns voices, and synthesizes audio automatically

Features

Voice Generation

• Voice Clone: Clone any voice with just a 3-second audio sample
• Custom Voice: 9 preset voices with style control (Vivian, Serena, Ryan, etc.)
• Voice Design: Describe your desired voice in natural language
• 10 Language Support: Korean, English, Chinese, Japanese, German, French, Russian, Portuguese, Spanish, Italian

Podcast Generation

• One-Click Podcasts: Enter a topic, get a complete podcast
• AI Script Writing: GPT-powered outline and transcript generation
• Multi-Speaker Support: Assign different voices to each speaker
• Custom Personas: Create and save speaker personalities

Quality of Life

• Parameter Presets: Quick presets for different use cases
• Generation History: Browse, search, and replay past generations
• Auto-Save Settings: Your preferences persist across sessions
• Real-time Feedback: Character count, generation time, and status indicators

Requirements

• Python 3.12+
• macOS (MPS) / Linux (CUDA)
• 16GB+ RAM
• OpenAI API Key (for Podcast feature)

Installation

1. Clone Repository

git clone https://github.com/bc-dunia/qwen3-TTS-studio.git
cd qwen3-TTS-studio

2. Create Virtual Environment

conda create -n qwen3-tts python=3.12 -y
conda activate qwen3-tts

3. Install Dependencies

pip install -U qwen-tts
pip install gradio soundfile numpy moviepy openai

For CUDA users:

pip install -U flash-attn --no-build-isolation

4. Download Models

Download models from HuggingFace or ModelScope.

HuggingFace (Recommended)

pip install -U "huggingface_hub[cli]"

# Required models
huggingface-cli download Qwen/Qwen3-TTS-Tokenizer-12Hz --local-dir ./Qwen3-TTS-Tokenizer-12Hz
huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-Base --local-dir ./Qwen3-TTS-12Hz-1.7B-Base
huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --local-dir ./Qwen3-TTS-12Hz-1.7B-CustomVoice

# Optional models
huggingface-cli download Qwen/Qwen3-TTS-12Hz-0.6B-Base --local-dir ./Qwen3-TTS-12Hz-0.6B-Base
huggingface-cli download Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice --local-dir ./Qwen3-TTS-12Hz-0.6B-CustomVoice
huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign --local-dir ./Qwen3-TTS-12Hz-1.7B-VoiceDesign

ModelScope (For users in China)

pip install -U modelscope

modelscope download --model Qwen/Qwen3-TTS-Tokenizer-12Hz --local_dir ./Qwen3-TTS-Tokenizer-12Hz
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-Base --local_dir ./Qwen3-TTS-12Hz-1.7B-Base
modelscope download --model Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --local_dir ./Qwen3-TTS-12Hz-1.7B-CustomVoice

5. Environment Variables

Create a .env file:

OPENAI_API_KEY=your_openai_api_key_here

Usage

Start Server

python qwen_tts_ui.py

Open http://127.0.0.1:7860 in your browser.

Available Models

Preset Voices

Project Structure

qwen3-TTS-studio/
├── qwen_tts_ui.py              # Main entry point
├── config.py                   # Configuration
│
├── ui/                         # UI Components
│   ├── content_input.py        # Content input section
│   ├── draft_editor.py         # Draft editing
│   ├── draft_preview.py        # Outline/transcript preview
│   ├── persona.py              # Persona management UI
│   ├── progress.py             # Progress indicators
│   └── voice_cards.py          # Voice selection cards
│
├── podcast/                    # Podcast Generation
│   ├── orchestrator.py         # Main orchestration
│   ├── models.py               # Pydantic models
│   ├── outline.py              # AI outline generation
│   ├── transcript.py           # AI transcript generation
│   ├── prompts.py              # LLM prompts
│   └── session.py              # Session management
│
├── audio/                      # Audio Processing
│   ├── generator.py            # TTS generation
│   ├── batch.py                # Batch processing
│   ├── combiner.py             # Audio concatenation
│   └── model_loader.py         # Model loading
│
└── storage/                    # Data Persistence
    ├── history.py              # Podcast history
    ├── persona.py              # Persona storage
    ├── persona_models.py       # Persona models
    └── voice.py                # Voice management

Acknowledgments

This project is built on top of the excellent Qwen3-TTS model by Alibaba Qwen team.

• HuggingFace: https://huggingface.co/collections/Qwen/qwen3-tts
• ModelScope: https://modelscope.cn/collections/Qwen/Qwen3-TTS
• Paper: https://arxiv.org/abs/2601.15621
• Blog: https://qwen.ai/blog?id=qwen3tts-0115

License

This project uses Qwen3-TTS models. Please refer to the Qwen3-TTS License for model usage terms.