This repository contains a web application for conducting AI-proctored interviews, built using Python for the backend and React for the frontend. The application incorporates various features such as cheating detection 🚫, answer validation ✅, video recording 📹, speech-to-text conversion 🗣️➡️💬, and scoring based on language proficiency and answer correctness. 🏆

• AI Proctored Cheating Detection System 🕵️‍♀️: Employs pose estimation techniques to detect and prevent cheating during interviews.
• Answer Validation System 👩‍🏫: Utilizes the OpenAI GPT API and a MongoDB question database to cross-check and validate interviewee answers.
• Video Recording and Speech-to-Text Conversion 📹➡️💬: Records video and converts speech to text using speech recognition technology.
• Scoring System 🏆: Scores interviewees based on their language proficiency, word choice, verb usage, and answer correctness, leveraging the OpenAI GPT API's feedback mechanism.
• AWS Services Integration ☁️: Utilizes various AWS services for hosting, storage, and other functionalities.

• Python 🐍: Backend development using Python and Flask web framework.
• React ⚛️: Frontend development with React, a popular JavaScript library for building user interfaces.
• OpenAI GPT API 🧠: Utilized for answer validation and scoring based on language proficiency and correctness.
• MongoDB 🍃: NoSQL database for storing interview questions and related data.
• AWS Services ☁️: Integration with various AWS services like EC2, S3, and others for hosting, storage, and other functionalities.
• Computer Vision Libraries 👀: Pose estimation and cheating detection using computer vision libraries like OpenCV or MediaPipe.
• Speech Recognition Libraries 🗣️➡️💬: Converting speech to text using libraries like SpeechRecognition or Google Cloud Speech-to-Text.

1. Clone the repository:

git clone https://github.com/JaynouOliver/ai-proctored-interviews.git

2. Install the required dependencies for the backend and frontend:

# Backend
cd backend
pip install -r requirements.txt

# Frontend
cd ../frontend
npm install

3. Set up the necessary configurations, including MongoDB connection details, OpenAI API key, and AWS credentials. 🔑

4. Start the backend and frontend servers:

# Backend
python app.py

# Frontend
npm start

5. Access the application by visiting http://localhost:3000 in your web browser. 🌐

Contributions are welcome! Please follow the standard GitHub workflow:

1. Fork the repository 🍴
2. Create a new branch for your feature or bug fix 🌳
3. Commit your changes 💻
4. Push your changes to your forked repository 🔄
5. Submit a pull request 📤