International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
Skillup Bot: An AI Driven Mock Interview Platform Shashank Rai1, Alisha Miranda2, Samiya Jagirdar3, Prof. Nidhi Chitalia4 1BE student, Department of Information Technology St. Francis Institute of Technology Mumbai, India 2BE student, Department of Information Technology St. Francis Institute of Technology Mumbai, India 3BE student, Department of Information Technology St. Francis Institute of Technology Mumbai, India 4Professor, Department of Information Technology St. Francis Institute of Technology Mumbai, India
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Abstract - In the contemporary job market, preparation
for interviews is a pivotal determinant of success in securing desired employment opportunities. To address this critical need, we introduce a comprehensive mock interview platform aimed at empowering candidates in their preparation journey. Our platform incorporates an array of advanced functionalities harnessing state-of-the-art artificial intelligence (AI) technologies to deliver an immersive and effective preparation experience. Central to our platform is the utilization of AI-driven video and audio analy- sis, providing candidates with real-time feedback on their interview performance. Through sophisticated machine learning (ML) algorithms, we offer nuanced assessments of various elements including communication skills, body language, and tone of voice. This enables candidates to gain valuable insights into their strengths and areas for improvement, enhancing their overall interview readiness. Moreover, our platform features a dynamic resume builder tool, enabling can- didates to craft personalized resumes tailored to specific job opportunities. This empowers candidates to present themselves in the best possible light, aligning their skills and experiences with the requirements of prospective employers. Additionally, we integrate a programming quiz platform designed to assess candidates’ technical proficiency, particularly relevant for roles in the IT and software development sectors. By offering a diverse range of evaluation tools, our platform caters to the multifaceted nature of modern job interviews, addressing both technical and soft skills requirements. Following completion of interview simulations and technical assessments, candidates receive comprehensive performance reports based on the analysis conducted by our ML algorithms. These reports serve as valuable insights, guiding candidates in their ongoing preparation efforts and facilitating continuous improvement.
In the contemporary landscape of career development, mock interviews play a crucial role beyond mere simulation, serving as an indispensable tool for honing the skills and fortitude needed to navigate the competitive job market successfully. This report explores the necessity of mock interviews, highlighting their significance in bridging the gap between academic qualifications and the dynamic expectations of employers, who seek candidates with adept communication, problem-solving, and interpersonal skills. A major challenge in interview preparation is the fragmented nature of available resources, necessitating candidates to navigate multiple platforms for comprehensive preparation. To address this challenge, our project consolidates interview preparation resources into a single platform, offering a diverse range of tools and functionalities such as AI-driven video and audio analysis, resume building, and programming quizzes. This integrated approach saves time, reduces frustration, and enhances the overall preparation experience for candidates. We aim to empower individuals for success in the competitive job market by providing a transformative solution - a dynamic and immersive platform that identifies weaknesses and cultivates strengths. Our motivation lies in reshaping the trajectory of individuals’ careers, enabling them to navigate interviews with poise, competence, and heightened selfassurance. The research objectives of our project include integrating advanced audio-video sentiment analysis, developing a robust resume builder, and implementing an interactive coding platform to enhance interview preparation. The project also aims to address gaps identified in existing literature, as evidenced by references such as [2]-[5].
2. LITERATURE REVIEW
Key Words: Mock Interview Platform; Self Evaluating Platform; Resume Builder Tool; Communication Skill Assessment; Machine learning; Technical Quiz Platform; Facial Emotion Recognition; Tone Analysis
© 2024, IRJET
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Impact Factor value: 8.226
We have consulted numerous research papers to underpin our work. A notable paper [1] presents an inventive Interviewee Performance Analyzer incorporating facial emotion and speech fluency recognition. The system integrates HaarCascade, Gabor filters, and Convolution Neural Network for facial emotion, and Mel frequency cepstral coefficient features with logistic regression for
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