voice-bridge-light（语音桥灯）

Voice Bridge Light

Lightweight offline voice bridging service providing OpenAI-compatible STT/TTS HTTP API.

Features

• TTS Text-to-Speech: Supports Edge TTS (online) and Piper (local)
• STT Speech Recognition: Based on Whisper local recognition
• OpenAI Compatible API: Compatible with OpenAI Audio API
• Lightweight Deployment: Minimal dependencies, easy to install

Usage

Installation

pip install -r requirements.txt

Start Service

Default using Edge TTS:

python api_server.py

Using Piper (model required):

TTS_ENGINE=piper PIPER_MODEL=models/piper/zh_CN-huayan-medium.onnx python api_server.py

API Endpoints

Configuration Environment Variables

TTS Request Example

curl -X POST http://localhost:18790/audio/speech \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Hello, world!",
    "voice": "zh-CN-XiaoxiaoNeural",
    "response_format": "mp3"
  }' \
  --output speech.mp3

STT Request Example

curl -X POST http://localhost:18790/audio/transcriptions \
  -F "file=@speech.mp3" \
  -H "Content-Type: multipart/form-data"

OpenClaw Integration

Configure in openclaw.json:

{
  "tts": {
    "enabled": true,
    "provider": "local-piper",
    "baseUrl": "http://127.0.0.1:18790",
    "apiKey": "local",
    "voice": "zh-CN-XiaoxiaoNeural"
  }
}

Dependencies

• Python 3.8+
• edge-tts (Edge TTS)
• faster-whisper (Whisper STT)
• soundfile (audio processing)
• Flask + Flask-CORS (web service)

Service Management

systemd Service (Recommended)

[Unit]
Description=Voice Bridge Light - STT/TTS HTTP API
After=network.target

[Service]
Type=simple
User=root
WorkingDirectory=/root/.openclaw/workspace/skills/voice-bridge-light
ExecStart=/usr/bin/python3 api_server.py
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target

Enable and start:

systemctl daemon-reload
systemctl enable voice-bridge-light.service
systemctl start voice-bridge-light.service

Performance

• TTS latency: < 1s (Edge TTS requires network)
• STT latency: depends on audio length, real-time CPU
• Memory usage: ~300-500MB (mainly from Whisper model)

Notes

• Edge TTS requires internet access to Microsoft services
• Piper requires downloading model files (first use)
• Whisper model loads slowly on first run, recommend warm-up
• Production environment recommended to use systemd management

License

MIT