qwen3-tts
# Qwen3-TTS VoiceDesign
Text → Speech with natural language voice descriptions + seed-based timbre fixation.
## Quick Start
```bash
# Generate speech (uses server defaults)
TTS_URL=http://your-server:8881 scripts/say.sh "Hello world!"
# Save to file
scripts/say.sh "Save this" output.mp3
# Batch compare seeds (voice exploration)
scripts/batch_seeds.sh "Hello world!" 42 123 201 456 789 /tmp/seeds
```
## Environment Variables
All config via env vars — text is the only required argument:
| Variable | Default | Description |
|----------|---------|-------------|
| `TTS_URL` | `http://localhost:8881` | Server base URL (client side) |
| `TTS_SEED` | `4096` | Random seed → controls timbre |
| `TTS_INSTRUCT` | (generic female voice) | Voice description prompt |
| `TTS_MODEL_PATH` | `Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign` | Model weights path |
| `TTS_PORT` | `8881` | Server listen port |
| `TTS_HOST` | `0.0.0.0` | Server bind address |
| `TTS_FORMAT` | `mp3` | Output format: `mp3` / `wav` |
Server reads from `.env` file in its directory. Client scripts read from shell env.
## Voice Description Example
```
30岁男性播音员，声音低沉磁性，
语速稳重从容，咬字清晰标准，
像新闻联播主播的专业感，又带一点温暖。
```
> **Tip:** Once you've found your perfect voice (description + seed), set them as server defaults in `.env`. Then client calls only need to pass `text`.
## API
### OpenAI-Compatible
```bash
curl -X POST $TTS_URL/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{"input": "Hello!"}' -o speech.mp3
```
### Custom (seed + instruct override)
```bash
curl -X POST $TTS_URL/tts \
-H "Content-Type: application/json" \
-d '{"text": "Hello!", "seed": 201, "instruct": "温柔女生"}' -o speech.mp3
```
### GET (quick test)
```bash
curl "$TTS_URL/tts?text=Hello&seed=201" -o test.mp3
```
## Seed Mechanics
Same `(description + seed)` → same timbre. Different seeds → completely different voices.
⚠️ **Seeds are purely random** — seed 42 and 43 can sound completely different. Finding a voice = opening blind boxes.
**Workflow:** fix description → batch 30-40 seeds → listen → shortlist 2-3 → compare across scenarios → pick.
## Deploy Your Own
```bash
# One-click setup (Python 3.10+ and CUDA GPU required)
bash scripts/setup.sh ./my-tts
# Configure voice in .env
echo 'TTS_SEED=201' >> ./my-tts/.env
echo 'TTS_INSTRUCT=Your voice description here' >> ./my-tts/.env
# Start server
bash scripts/setup.sh start ./my-tts
```
Setup installs: `qwen-tts`, `soundfile`, `pydub`, `uvicorn`, `fastapi`, `torch` (CUDA).
Downloads VoiceDesign model (~3.5GB) via ModelScope (China) or HuggingFace.
**Requirements:** CUDA GPU with 4GB+ VRAM, Python 3.10+, ~4GB disk.
## Scripts
| Script | Purpose |
|--------|---------|
| `scripts/say.sh` | Generate speech — `say.sh "text" [output.mp3]` |
| `scripts/batch_seeds.sh` | Compare seeds — `batch_seeds.sh "text" seed1 seed2 ...` |
| `scripts/tts_server.py` | FastAPI server (fully env-configurable) |
| `scripts/setup.sh` | One-click deploy (venv + deps + model download) |
## OpenClaw Integration
In `openclaw.json`:
```json
{
"env": { "OPENAI_TTS_BASE_URL": "http://<your-server>:8881/v1" },
"messages": {
"tts": {
"provider": "openai",
"openai": { "apiKey": "dummy", "model": "qwen3-tts", "voice": "default" },
"timeoutMs": 120000
}
}
}
```
## Server Management
```bash
# Health check
curl -s $TTS_URL/health
# Start (foreground)
python tts_server.py
# Start (background, Linux/macOS)
nohup python tts_server.py > server.log 2>&1 &
# Auto-restart (Windows — scheduled task + guard script)
# Create tts_guard.bat:
# @echo off
# :loop
# python tts_server.py
# timeout /t 10
# goto loop
# Register: schtasks /create /tn "TTS-Guard" /tr "tts_guard.bat" /sc onlogon /rl highest
# Auto-restart (Linux — systemd)
# See setup.sh output for systemd unit template
# Stop
# Linux/macOS: kill $(lsof -ti:8881)
# Windows: for /f "tokens=5" %a in ('netstat -aon ^| findstr :8881') do taskkill /PID %a /F
```
## Troubleshooting
- **Connection refused** → Server not running; start it
- **30s+ first request** → Cold start (model loading ~60s); subsequent requests 10-15s
- **Behind proxy** → Set `NO_PROXY=<server_ip>` on client side
- **Windows firewall** → `netsh advfirewall firewall add rule name="TTS" dir=in action=allow protocol=TCP localport=8881`
- **No flash-attn on Windows** → Expected; falls back to PyTorch SDPA (slower but works)
- **PowerShell corrupts Chinese** → Edit `.env`/config via Python or SCP, not PowerShell `Set-Content`
- **Process dies on SSH disconnect** → Use scheduled task (Windows) or systemd (Linux) instead of foreground
## Voice Design Tips
Describe like casting a voice actor:
- **Age/gender**: "18岁女大学生" / "30岁男性播音员"
- **Texture**: "柔和温暖" / "清脆明亮" / "低沉磁性"
- **Emotion**: "轻柔细腻" / "活泼开朗"
- **Accent**: "南方口音软糯" / "台湾腔" / "东北大碴子味"
- **Metaphor**: "像棉花糖" / "像播音主持" (helps the model capture feeling)
⚠️ **Timbre ≠ description.** Description controls style/emotion; seed controls timbre. Don't put personality traits ("灵动俏皮") in description — that's the seed's job.
标签
skill
ai
