Year: 2026
Type: article
Abstract: The recruitment process has undergone a major transformation with the rise of digital platforms and remote hiring practices. Despite this progress, traditional hiring systems still suffer from inefficiencies such as manual resume screening, subjective interview evaluation, lack of personalization, and lim-ited feedback for candidates. These challenges lead to increased recruitment costs, biased decision-making, and poor candidate preparedness. This paper presents InterviewXpert, an AI-driven automated interview and resume analysis system designed to enhance recruitment efficiency and interview preparedness. In-terviewXpert provides intelligent job recommendations, person-alized mock interviews, real-time interview question generation based on resumes and job descriptions, automated video-based answer evaluation, recruiter-driven assessments, and detailed performance reports. The system integrates Natural Language Processing (NLP), Large Language Models (LLMs), speech-to-text processing, and computer vision techniques to analyze both the content and delivery of candidate responses. The proposed system benefits candidates by offering realistic interview simula-tions, actionable feedback, resume-building assistance, and career guidance, while recruiters gain tools for job posting, candidate assessment, interview evaluation, and shortlisting.
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7165879550
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