MoodMeter.AI is designed to enhance online communication in remote work environments by providing real-time emotional intelligence. Utilizing facial expression and voice analysis, our tool offers insights into the emotional state of meeting participants, fostering better understanding and collaboration in online meetings.

• Real-Time Emotion Detection: Leverages machine learning to analyze facial expressions and voice tones, offering instant feedback on the emotional state of participants.
• Facial Expression Analysis: Uses advanced facial recognition technology to interpret non-verbal cues, essential for understanding nuanced communication.
• Voice Sentiment Analysis: Processes vocal inputs to determine sentiment, aiding in the perception of tone and intent.
• Interactive Dashboard: Provides a user-friendly interface with real-time analytics and summaries of emotional cues.

• React.js: Ensures a dynamic and responsive user interface, catering to interactive user experiences.
• Node.js and Express.js: Creates a robust server-side architecture that is scalable and efficient.
• Python: Powers our advanced machine learning models for accurate and fast sentiment analysis.
• Agora SDK: Enables real-time video communication, essential for analyzing online meeting interactions.
• LLM (Language Learning Models): Utilized for sophisticated text summarization and sentiment analysis, enhancing the accuracy of our emotion detection algorithms.

• Install Dependencies: Navigate to the project directory and run npm install to install all required dependencies.

$ cd client && npm install

• Environment Setup: Configure the .env file with necessary API keys and settings.

Agora_API = "INSERT YOUR API KEY"

• Launch the Application: In a separate terminal, execute npm start to launch the React application.

$ npm run-script start

• Access the Application: Open a web browser and visit http://localhost:3000 to access MoodMeter.AI.

• Join a Meeting: Log into the platform and join an online meeting.
• Enable Emotion Analysis: Activate the emotion detection feature to start analyzing the emotional state of participants.
• View Insights: Real-time emotional insights are displayed on the dashboard, offering an enhanced understanding of the meeting dynamics.

We welcome contributions to MoodMeter.AI! If you're interested in improving our application or adding new features, please follow these steps:

Fork the Repository: Create a personal fork of the project on GitHub. Create a New Branch: For each new feature or improvement, create a separate branch. Submit a Pull Request: After making your changes, submit a pull request for review.