EmotionAware-AI

EmotionAware-AI is an open-source project designed to detect and interpret human emotions through facial expressions and speech analysis. By leveraging advanced machine learning techniques, this system aims to enhance human-computer interactions by providing emotionally intelligent responses.

Features

• Facial Emotion Recognition: Analyzes facial expressions to identify emotions such as happiness, sadness, anger, surprise, and more.
• Speech Emotion Recognition: Processes vocal inputs to detect emotional states conveyed through tone and pitch.
• Real-time Processing: Capable of analyzing and responding to emotional cues in real-time.
• Modular Architecture: Organized into distinct components for facial analysis (face), speech analysis (speech), backend processing (backend), and frontend interface (frontend).

Installation

To set up the EmotionAware-AI project locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/Priyanchew/EmotionAware-AI.git

2. Navigate to the Project Directory:

   cd EmotionAware-AI

3. Install Dependencies:

   • Backend and Speech Analysis:

     Navigate to the respective directories and install the required Python packages:

     cd backend
     pip install -r requirements.txt

     cd ../speech
     pip install -r requirements.txt

   • Frontend:

     Navigate to the frontend directory and install the necessary Node.js packages:

     cd ../frontend
     npm install

4. Run the Application:

   • Backend:

     cd ../backend
     python app.py

   • Frontend:

     In a new terminal window:

     cd frontend
     npm start

Usage

Once the application is running:

1. Access the Frontend Interface:

   Open your web browser and navigate to http://localhost:3000 to interact with the EmotionAware-AI system.

2. Emotion Detection:

   • Facial Analysis: Use your device's camera to allow the system to analyze your facial expressions.
   • Speech Analysis: Provide vocal input through your device's microphone for speech emotion recognition.

3. Real-time Feedback:

   The system will display the detected emotions in real-time, providing insights into the emotional state conveyed through facial expressions and speech.

Contributing

Contributions to EmotionAware-AI are welcome. To contribute:

1. Fork the Repository:

   Click on the 'Fork' button at the top right corner of the repository page.

2. Create a New Branch:

   git checkout -b feature/your-feature-name

3. Make Your Changes:

   Implement your feature or fix and commit the changes with a descriptive message.

4. Push to Your Fork:

   git push origin feature/your-feature-name

5. Submit a Pull Request:

   Navigate to the original repository and click on 'New Pull Request' to submit your changes for review.

License

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

Acknowledgments

Special thanks to the contributors and the open-source community for their invaluable support and resources.

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Note: For optimal performance, ensure that your device has a functional camera and microphone. The application may require permissions to access these devices.

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