feat: TTS personality engine (Issue #494)
Implement context-aware text-to-speech with emotion-driven expression for SaltyBot.
Features:
✓ Context-aware greetings (time of day, person names, emotion)
✓ Priority queue management (safety > social > idle)
✓ Emotion-based rate/pitch modulation (happy: faster+higher, sad: slower+lower)
✓ Integration with emotion engine (Issue #429) and TTS service (Issue #421)
✓ Configurable personality parameters
✓ Person recognition for personalized responses
✓ Queue management with 16-item buffer
Architecture:
Node: tts_personality_node
- Subscribes: /saltybot/tts_request, /saltybot/emotion_state, /saltybot/person_detected
- Publishes: /saltybot/tts_command (formatted for TTS service), /saltybot/personality_state
- Runs worker thread for asynchronous queue processing
Personality Parameters:
- Name: "Luna" (default, configurable)
- Speed modulation: happy=1.1x, sad=0.9x, neutral=1.0x
- Pitch modulation: happy=1.15x, sad=0.85x, neutral=1.0x
- Time-based greetings for 4 periods (morning, afternoon, evening, night)
- Known people mapping for personalization
Queue Priority Levels:
- SAFETY (3): Emergency/safety messages
- SOCIAL (2): Greetings and interactions
- IDLE (1): Commentary and chatter
- NORMAL (0): Default messages
Files Created:
- saltybot_tts_personality package with main personality node
- config/tts_personality_params.yaml with configurable parameters
- launch/tts_personality.launch.py for easy startup
- Unit tests for personality context and emotion handling
- Comprehensive README with usage examples
Integration Points:
- Emotion engine (Issue #429): Listens to emotion updates
- TTS service (Issue #421): Publishes formatted commands
- Jabra SPEAK 810: Output audio device
- Person tracking: Uses detected person names
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
sl-mechanical
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