Oratriq - AI Presentation Skills Coach

An AI-powered application that uses computer microphone input to convert speech to text and generate recommendations for improving presentation skills.

Project Overview

This application provides real-time feedback on presentation skills by:

• Capturing audio from the computer's microphone
• Converting speech to text using AI
• Analyzing presentation patterns and delivery
• Generating actionable recommendations for improvement

Project Structure

oratriq/
├── README.md                 # Project documentation
├── requirements.txt          # Python dependencies
├── .gitignore               # Git ignore patterns
├── .env.example             # Environment variables template
├── .cursor/                 # Cursor IDE configuration
│   └── rules/
│       └── project-rules.mdc # Project coding standards and guidelines
├── config/
│   ├── __init__.py
│   └── settings.py          # Application configuration
├── src/
│   ├── __init__.py
│   ├── main.py              # Main CLI entry point
│   ├── audio/
│   │   ├── __init__.py
│   │   ├── recorder.py      # Audio recording functionality
│   │   └── processor.py     # Audio processing utilities
│   ├── speech/
│   │   ├── __init__.py
│   │   ├── stt.py          # Speech-to-text conversion
│   │   └── analyzer.py     # Speech analysis
│   ├── ai/
│   │   ├── __init__.py
│   │   ├── recommender.py  # AI recommendation engine
│   │   └── models.py       # AI model configurations
│   └── utils/
│       ├── __init__.py
│       ├── logger.py       # Logging utilities
│       └── helpers.py      # General helper functions
├── tests/
│   ├── __init__.py
│   ├── test_audio.py
│   ├── test_speech.py
│   └── test_ai.py
└── data/
    ├── recordings/         # Audio recordings (gitignored)
    └── transcripts/        # Speech transcripts (gitignored)

Features

Phase 1 (MVP - Command Line Interface)

• Real-time microphone audio capture
• Speech-to-text conversion
• Basic presentation analysis
• Command-line recommendations output

Phase 2 (Enhanced Features)

• Advanced speech pattern analysis
• Confidence scoring
• Historical performance tracking
• Export reports

Phase 3 (Advanced Features)

• Real-time feedback during presentations
• Integration with presentation software
• Web interface
• Multi-language support

Technology Stack

• Python 3.8+: Core application language
• Speech Recognition: Audio processing and STT
• OpenAI API: Advanced text analysis and recommendations
• PyAudio: Audio recording and playback
• Click: Command-line interface framework
• Pydantic: Data validation and settings management

Development Guidelines

Code Style

• Follow PEP 8 style guidelines
• Use type hints for all function parameters and return values
• Maximum line length: 88 characters (Black formatter)
• Use meaningful variable and function names

Testing

• Write unit tests for all modules
• Maintain minimum 80% code coverage
• Use pytest for testing framework
• Mock external dependencies in tests

Documentation

• Use docstrings for all public functions and classes
• Follow Google docstring format
• Keep README updated with new features
• Document API endpoints and configuration options

Error Handling

• Implement comprehensive error handling
• Use custom exception classes for domain-specific errors
• Log errors with appropriate levels
• Provide user-friendly error messages

Getting Started

Prerequisites

• Python 3.8 or higher
• Microphone access
• OpenAI API key (for advanced features)

Installation

1. Clone the repository
2. Create a virtual environment: python -m venv venv
3. Activate the virtual environment:
   • Windows: venv\Scripts\activate
   • macOS/Linux: source venv/bin/activate
4. Install dependencies: pip install -r requirements.txt
5. Copy .env.example to .env and configure your settings
6. Run the application: python src/main.py

Usage

Basic Usage

# Start a presentation session
python src/main.py start

# Analyze a recorded audio file
python src/main.py analyze --file path/to/recording.wav

# Get help
python src/main.py --help

Configuration

The application can be configured through:

• Environment variables (see .env.example)
• Configuration file (config/settings.py)
• Command-line arguments

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes following the coding guidelines
4. Add tests for new functionality
5. Update documentation as needed
6. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support and questions, please open an issue on the GitHub repository.