SkillMirror: An AI-Based Communication and Interview Training Platform Using Speech and Computer Vision Analysis

Abstract: Effective communication and interview skills are essential for student employability, yet traditional training methods often lack personalization and real-time feedback. This paper presents SkillMirror, an AI-based communication and interview training platform that enhances both verbal and non-verbal skills through a multimodal analysis approach. The system simulates interview scenarios where user responses are captured via audio and video. Speech-to-text and natural language processing techniques are employed to evaluate grammar, fluency, and linguistic coherence, while computer vision methods analyze non-verbal cues such as facial expressions, posture, and eye contact. Based on these analyses, the platform provides real-time feedback, performance metrics, and personalized improvement suggestions.

Additionally, the system includes a quiz module for knowledge assessment and a feedback module for progress tracking and motivation. By integrating speech processing and behavioral analysis, SkillMirror offers a scalable and intelligent solution for improving communication skills and interview readiness.

Keywords: Artificial Intelligence, Interview Training, Speech-to-Text, Natural Language Processing, Computer Vision, Multimodal Analysis, Communication Skills, Real Time FeedbackVision, Multimodal Analysis, Communication Skills, Real-Time Feedback