AI-BASED BODY LANGUAGE ANALYSIS FOR INTERVIEW FEEDBACK

ABSTRACT: Body language is a vital communication component, particularly in job interviews, where non-verbal cues significantly influence a candidate’s perception and evaluation. This project proposes an AI-powered system that analyzes candidates’ body language during interviews to deliver structured feedback. Leveraging computer vision and machine learning, the system evaluates facial expressions, gestures, posture, and eye contact to assess confidence, engagement, and professionalism. By processing video inputs, it extracts behavioral patterns and generates personalized, data-driven insights to help candidates improve their non-verbal communication. The system benefits job seekers, HR professionals, and training institutions by offering unbiased, automated feedback to identify strengths and areas for improvement—promoting more effective interview preparation and decision-making. Keywords: Body Language, Interview Feedback, Machine Learning, Computer Vision, Posture Analysis, Facial Expression Recognition.

Authors

Publication Details

Journal
International Scientific Journal of Engineering and Management
Published
2025-05-07
DOI
https://doi.org/10.55041/isjem03424
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
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article

AI-BASED BODY LANGUAGE ANALYSIS FOR INTERVIEW FEEDBACK

Swetha Sailaja
International Scientific Journal of Engineering and Management
Emotion and Mood Recognition
article

AI-BASED BODY LANGUAGE ANALYSIS FOR INTERVIEW FEEDBACK

Swetha Sailaja
article en

Abstract

ABSTRACT: Body language is a vital communication component, particularly in job interviews, where non-verbal cues significantly influence a candidate’s perception and evaluation. This project proposes an AI-powered system that analyzes candidates’ body language during interviews to deliver structured feedback. Leveraging computer vision and machine learning, the system evaluates facial expressions, gestures, posture, and eye contact to assess confidence, engagement, and professionalism. By processing video inputs, it extracts behavioral patterns and generates personalized, data-driven insights to help candidates improve their non-verbal communication. The system benefits job seekers, HR professionals, and training institutions by offering unbiased, automated feedback to identify strengths and areas for improvement—promoting more effective interview preparation and decision-making. Keywords: Body Language, Interview Feedback, Machine Learning, Computer Vision, Posture Analysis, Facial Expression Recognition.

International Scientific Journal of Engineering and ManagementVol. 04(05)
Openalex Percentile: Top 90%
Emotion and Mood Recognition
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