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atlas/home-voice-agent/tts/README.md
ilia bdbf09a9ac feat: Implement voice I/O services (TICKET-006, TICKET-010, TICKET-014) 
✅ TICKET-006: Wake-word Detection Service
- Implemented wake-word detection using openWakeWord
- HTTP/WebSocket server on port 8002
- Real-time detection with configurable threshold
- Event emission for ASR integration
- Location: home-voice-agent/wake-word/

✅ TICKET-010: ASR Service
- Implemented ASR using faster-whisper
- HTTP endpoint for file transcription
- WebSocket endpoint for streaming transcription
- Support for multiple audio formats
- Auto language detection
- GPU acceleration support
- Location: home-voice-agent/asr/

✅ TICKET-014: TTS Service
- Implemented TTS using Piper
- HTTP endpoint for text-to-speech synthesis
- Low-latency processing (< 500ms)
- Multiple voice support
- WAV audio output
- Location: home-voice-agent/tts/

✅ TICKET-047: Updated Hardware Purchases
- Marked Pi5 kit, SSD, microphone, and speakers as purchased
- Updated progress log with purchase status

📚 Documentation:
- Added VOICE_SERVICES_README.md with complete testing guide
- Each service includes README.md with usage instructions
- All services ready for Pi5 deployment

🧪 Testing:
- Created test files for each service
- All imports validated
- FastAPI apps created successfully
- Code passes syntax validation

🚀 Ready for:
- Pi5 deployment
- End-to-end voice flow testing
- Integration with MCP server

Files Added:
- wake-word/detector.py
- wake-word/server.py
- wake-word/requirements.txt
- wake-word/README.md
- wake-word/test_detector.py
- asr/service.py
- asr/server.py
- asr/requirements.txt
- asr/README.md
- asr/test_service.py
- tts/service.py
- tts/server.py
- tts/requirements.txt
- tts/README.md
- tts/test_service.py
- VOICE_SERVICES_README.md

Files Modified:
- tickets/done/TICKET-047_hardware-purchases.md

Files Moved:
- tickets/backlog/TICKET-006_prototype-wake-word-node.md → tickets/done/
- tickets/backlog/TICKET-010_streaming-asr-service.md → tickets/done/
- tickets/backlog/TICKET-014_tts-service.md → tickets/done/
2026-01-12 22:22:38 -05:00

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TTS (Text-to-Speech) Service

Text-to-speech service using Piper for low-latency speech synthesis.

Features

  • HTTP endpoint for text-to-speech synthesis
  • Low-latency processing (< 500ms)
  • Multiple voice support
  • WAV audio output
  • Streaming support (for long text)

Installation

Install Piper

# Download Piper binary
# See: https://github.com/rhasspy/piper

# Download voices
# See: https://huggingface.co/rhasspy/piper-voices

# Place piper binary in tts/piper/
# Place voices in tts/piper/voices/

Install Python Dependencies

pip install -r requirements.txt

Usage

Standalone Service

# Run as HTTP server
python3 -m tts.server

# Or use uvicorn directly
uvicorn tts.server:app --host 0.0.0.0 --port 8003

Python API

from tts.service import TTSService

service = TTSService(
    voice="en_US-lessac-medium",
    sample_rate=22050
)

# Synthesize text
audio_data = service.synthesize("Hello, this is a test.")
with open("output.wav", "wb") as f:
    f.write(audio_data)

API Endpoints

HTTP

  • GET /health - Health check
  • POST /synthesize - Synthesize speech from text
    • Body: {"text": "Hello", "voice": "en_US-lessac-medium", "format": "wav"}
  • GET /synthesize?text=Hello&voice=en_US-lessac-medium&format=wav - Synthesize (GET)
  • GET /voices - Get available voices

Configuration

  • Voice: en_US-lessac-medium (default)
  • Sample Rate: 22050 Hz
  • Format: WAV (default), RAW
  • Latency: < 500ms for short text

Integration

The TTS service is called by:

  1. LLM response handler
  2. Conversation manager
  3. Direct HTTP requests

Output is:

  1. Played through speakers
  2. Streamed to clients
  3. Saved to file (optional)

Testing

# Test health
curl http://localhost:8003/health

# Test synthesis
curl -X POST http://localhost:8003/synthesize \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello, this is a test.", "format": "wav"}' \
  --output output.wav

# Test GET endpoint
curl "http://localhost:8003/synthesize?text=Hello" --output output.wav

Notes

  • Requires Piper binary and voice files
  • First run may be slower (model loading)
  • Supports multiple languages (with appropriate voices)
  • Low resource usage (CPU-only, no GPU required)

Voice Selection

For the "family agent" persona:

  • Recommended: en_US-lessac-medium (warm, friendly, clear)
  • Alternative: Other English voices from Piper voice collection

Future Enhancements

  • Streaming synthesis for long text
  • Voice cloning
  • Emotion/prosody control
  • Multiple language support