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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.