An AI-powered application that acts as a personal public speaking advisor. Upload a video of yourself speaking, and the AI will perform a holistic analysis of your communication skills, providing a comprehensive report with actionable feedback to help you improve.

• Multimodal Analysis: The coach analyzes both verbal and non-verbal communication channels:

  • 🎭 Visual Analysis: Detects facial expressions and emotions through computer vision techniques
  • 👁️ Eye Contact: Measures how consistently you look at the camera
  • 📝 Speech Analysis: Transcribes speech and analyzes pacing (WPM), use of filler words, and sentiment

• Comprehensive Reports: Generate detailed assessments with:

  • 📊 Emotion Distribution: Visual radar charts showing expression variety
  • 📈 Speech Metrics: Word count, pace, filler word frequency
  • 🖼️ Expression Samples: Visual examples of your different facial expressions

• Actionable Feedback: Receive personalized suggestions for improvement in:

  • 🗣️ Speaking Style: Pace, filler word reduction, speech clarity
  • 😊 Emotional Expression: Expressiveness, variety, appropriateness
  • 📹 Camera Presence: Positioning, eye contact, engagement

This project orchestrates several state-of-the-art open-source technologies:

• Backend:Python
• AI / Machine Learning:
  • Speech Recognition:openai-whisper for accurate speech-to-text
  • Sentiment Analysis: Hugging Face transformers for text sentiment evaluation
  • Computer Vision:OpenCV for face detection and expression analysis
• Visualization:matplotlib for data visualization and charting
• Frontend Interface:gradio for interactive web UI
• Media Processing:ffmpeg-python for audio extraction

The application follows a streamlined data processing pipeline:

graph TD A[🎥 Video Upload] --> B{Extract Audio}; B --> C[🎧 Audio File]; A --> D[🎞️ Video Frames]; subgraph "Parallel Analysis" D --> E[👁️ OpenCV: Facial Analysis & Emotion Detection]; C --> G[📝 Whisper: Speech-to-Text]; end G --> H[🧐 Text Analysis: Pace, Fillers, Sentiment]; subgraph "Data Integration" E --> I{🧠 Analysis Engine}; H --> I; end I --> J[📊 Generate Visual Reports & Suggestions]; J --> K[🖥️ Display in Gradio Interface]; 

• Python 3.8+
• FFmpeg installed on your system

1. Clone the repository:

git clone https://github.com/yourusername/ai-communication-coach.git cd ai-communication-coach

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the application:

python app.py

The web interface will be available at http://localhost:7860

1. Upload Your Video: Use the upload button or record directly in your browser
2. Wait for Processing: The AI will analyze your video (this may take a few moments)
3. Review Your Report: Explore the comprehensive analysis of your presentation
4. Implement Feedback: Apply the personalized suggestions to improve your skills

The AI Communication Coach provides a detailed assessment including:

• Speech Transcription: Full text of your presentation
• Sentiment Analysis: The emotional tone of your words
• Speaking Pace: Words per minute compared to ideal ranges
• Filler Word Detection: Frequency and types of verbal fillers
• Facial Expression Analysis: Distribution of emotions detected
• Eye Contact Measurement: Consistency of camera engagement
• Visual Presence: Assessment of positioning and framing

Contributions are welcome! If you'd like to improve the AI Communication Coach:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add some amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

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

• OpenAI Whisper for speech recognition
• Hugging Face Transformers for sentiment analysis
• OpenCV for computer vision capabilities
• Gradio for the interactive web interface
• Matplotlib for data visualization

For questions or feedback, please open an issue on the GitHub repository.