AI-Driven Interview Assistance - Mock Interview Simulator

AI-Driven Interview Assistance is a full-stack, AI-powered mock interview simulation platform built with the MERN stack (MongoDB, Express.js, React.js, Node.js). The AI module is implemented using Python, leveraging natural language processing (NLP), machine learning (ML), and the Gemini API to dynamically generate questions, analyze responses, and provide actionable feedback. This platform empowers users to prepare for technical interviews through interactive sessions featuring real-time video/audio capture, intelligent question generation based on resume analysis, and personalized feedback.

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Table of Contents

• Preview
• Features
• Technologies Used
• Usage
• Architecture
• Deployment
• Team Members
• Contact
• Acknowledgments

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Preview

Upload your resume to begin the personalized interview session.

Real-time AI interview simulation with dynamic question generation and media recording.

Get detailed performance analytics and improvement suggestions.

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Features

🎯 Core Functionalities:

• Resume Upload & Parsing: Analyzes user resumes to extract skills and experience using NLP.
• AI-Driven Question Generation: Dynamically generates domain-relevant questions based on the user's resume using the Gemini API.
• Adaptive Interview Flow: Adjusts question difficulty in real-time based on user responses.
• Speech Interaction: Records and transcribes answers using Speech-to-Text APIs.
• AI Feedback Engine: Utilizes the Gemini API to provide constructive feedback on clarity, accuracy, and technical depth of answers.

💻 Frontend Highlights:

• Built with React.js and styled using CSS.
• Responsive Design compatible with desktop and mobile.
• Utilizes React Router for seamless navigation.
• Integrated MediaDevices API and Web Speech API for video/audio capture and transcription.

🔧 Backend Highlights:

• Express.js API to handle resume parsing, question generation, and feedback processing.
• MongoDB Atlas for secure and scalable data storage.
• Python-based AI module integrated with Gemini API for question and feedback logic.

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Technologies Used

• Frontend: React.js, CSS, React Router, MediaDevices API, Web Speech API
• Backend: Node.js, Express.js
• AI Module: Python (NLP, Machine Learning, Gemini API)
• Database: MongoDB Atlas
• Deployment: Vercel (Frontend), Render (Backend)
• Tools: Git, GitHub, Postman

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Usage

1. Start Interview: Access the platform and upload your resume (PDF).
2. Resume Analysis: Backend parses resume and identifies relevant skills.
3. Interactive Interview: AI starts asking questions via voice; you respond via video/audio.
4. Transcription & Evaluation: Responses are transcribed and sent to Gemini API for evaluation.
5. Receive Feedback: View insights on your performance and retry for improvement.

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Architecture

Frontend (React.js)
│
├── Resume Upload → Backend (Express)
├── Video/Audio Capture
├── Fetch AI Questions → Python AI Module (Gemini API)
└── Feedback Display ← Backend Evaluation

Backend (Node.js + Express)
│
├── Resume Parser
├── AI Question Generator ← Python + Gemini API
├── Response Evaluator ← Gemini API
└── MongoDB (Persistent Storage)

Team Members

This project was collaboratively developed as a final year engineering project by the following team members:

• 🎓 Dnayaneshvari Wakarekar – Team Leader (Project Coordination & Management)
• 👩‍💻 Nikita Jadhav – Frontend & Integration
• 👨‍💻 Rohan Bhoge – Python AI Module & AI API Integration
• 👨‍💻 Shreyash Shedage – Backend & Integration

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Contact

• Email: bhogerohan12@gmail.com
• GitHub: https://github.com/RohanBhoge
• LinkedIn: https://www.linkedin.com/in/rohanbhoge

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Acknowledgments

• Thanks to Gemini API, OpenAI, Web APIs, and the open-source developer community for their invaluable contributions.
• Inspired by real-world tech interview platforms and modern advancements in AI.
• Special thanks to our project guide Prof. Snehal Malpani at D.Y. Patil College of Engineering, Akurdi, Pune for their support and guidance.