Implementation of human-like conversational patterns for Virtual Humans, focusing on turn-taking, context awareness, response variation, and repair strategies.
This research project implements and validates key conversational patterns that contribute to more natural human-like interactions in AI systems. The implementation focuses on:
- Turn-taking mechanisms
- Context awareness
- Response variation
- Repair strategies
conversational_patterns/
├── src/
│ └── conversational_patterns/
│ ├── core/ # Core system components
│ ├── patterns/ # Pattern implementations
│ ├── utils/ # Utility functions
│ └── config/ # Configuration management
├── tests/
│ ├── unit/ # Unit tests
│ ├── integration/ # Integration tests
│ └── behavioral/ # Pattern-specific tests
├── docs/
│ ├── api/ # API documentation
│ └── architecture/ # Architecture decisions
└── scripts/ # Utility scripts
- Python 3.9 or higher
- Redis server
- Virtual environment tool
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Unix/macOS- Install the package with development dependencies:
pip install -e ".[dev]"- Run tests:
pytest- Run type checking:
mypy src- Format code:
black src tests
isort src testsMIT License