AI powerd mock interview bot using NLP and ML

The AI Mock Interview Bot is an interactive practice partner designed to simulate realistic job interviews across industries and seniority levels. It delivers structured questions, adapts to user responses in real-time, and provides precise, competency-based feedback. The bot can run interviews in different styles (behavioral, technical, system design, case study, product sense, culture fit) and aligns with frameworks commonly used in real hiring processes such as STAR, BAR, MECE, and interviewer rubrics.

1. B E Project Work - Presentation AMC Engineering College Department of Information Science and Engineering AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis Presented By : Karthish B M 1AM21IS049 Harsha H B 1AM22IS403 Dhanush G 1AM21IS031 Adithya S 1AM22IS401 Project Guide : Prof. Divya Tyagi Assistant Professor, Dept. of ISE

2. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 1. INTRODUCTION Interviews play a critical role in the hiring process, but many candidates face challenges such as lack of preparation, inability to handle behavioral questions, or nervousness. The AI-Powered Interview Mentor addresses these challenges by simulating real interview scenarios. It leverages deep learning techniques like transformer-based models for natural language processing to generate tailored questions and analyze user responses. Tools such as Deep Face are employed for emotion detection, while ML-based classifiers assess speech fluency and tone. By combining these advanced technologies, the system offers personalized feedback on language proficiency, technical knowledge, confidence, and emotional stability.

3. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 2. PROBLEM STATEMENT Preparing for interviews can be daunting, as candidates often struggle with both technical questions and behavioral aspects like confidence, body language, and communication skills. Existing tools fail to provide an integrated solution that analyzes technical proficiency, behavioral responses, and emotional cues. There is a need for an AI-based platform that can simulate real interviews, assess multiple factors, and offer actionable feedback for comprehensive preparation .

4. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 3. LITERATURE SURVEY Sl.no Title Authors Methodology Advantages Disadvantages Year 1 AI-Based mock interview evaluator: An emotion and confidence classifier model." Mandal, Rubi, Pranav Lohar, Dhiraj Patil, Apurva Patil, and Suvarna Wagh Mock interview can boost our confidence and communication skills which can help perform better Improved Efficiency, improved confidence analysis , Reduced Errors, improved questions. No resume-based question generation 2023 2 Interview Bot with Automatic Question Generation and Answer Evaluation Raj Pandey , Divya Chaudhari , Sahil Bhawani , Omkar Pawar , Sunita Barve Resume screening and interview chatbots are the basic requirements for today’s hiring processes for a given job post. There are a large number of candidates who apply and manually sorting these resumes as per the job requirement is a tedious task for shortlisting the candidates Automatic question generation ,Answer evaluation and Resume Screening Limited question generation 2023

5. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 4. EXISTING METHOD Predefined Questionnaires : Generic questions unrelated to specific roles or resumes. No Real-Time Features : Lack of live analysis for facial expressions, voice quality, and user engagement. Limited Personalization : Fails to tailor questions based on user profiles or job roles. Basic Feedback : Limited to evaluating correct answers without behavioral insights.

6. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 5. PROPOSED METHOD Role-Specific Questions : Voice Input Analysis : Real-Time Alerts : Post-Interview Report : Confidence Analysis: Facial Expression Analysis :

7. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis 5. IMPLEMENTATION Data Collection : Model Development : Preprocessing : System Integration : Feedback Mechanism: Web Interface Development: Testing and Validation : Deployment :

8. AI-Based Interview Mentor with Deep Learning for Behavioral and Technical Analysis Thank You