Abstract: The AI-based interview evaluator is a comprehensive system designed to provide an objective and data-driven assessment of candidates during job interviews. By leveraging cutting-edge technologies in machine learning, computer vision, and natural language processing, the system analyses video and audio inputs to evaluate a candidate's emotions, confidence, and knowledge. For emotion recognition, the system utilizes Deep face and Haar Cascade models, which can detect a wide range of facial expressions and subtle emotional cues. These models help determine the candidate's emotional state throughout the interview, providing valuable insights into their level of engagement and comfort. In addition, the system employs Google Speech Recognition for accurate speech-to-text conversion, allowing it to analyse the content of the candidate's responses. This feature enables the system to assess the candidate's communication skills, articulation, and knowledge of the subject matter. To evaluate the candidate's confidence levels, the system utilizes a Random Forest Classifier trained on datasets containing confident and non-confident speech patterns. By comparing the candidate's speech patterns against these datasets, the system can determine their level of confidence in their responses. Furthermore, a neural network-based chatbot is integrated into the system to provide a more interactive interview experience. The chatbot can ask follow-up questions, clarify doubts, and engage the candidate in a conversation, simulating a real-life interview scenario. Based on the analysis of the candidate's emotions, confidence, and knowledge, the system generates insights and suggestions to aid organizations in making informed hiring decisions. These insights can help identify candidates who are well-suited for the role and provide valuable feedback for candidates looking to improve their interview performance.
Keywords: AI Based Interview Evaluator, Facial Expression Analysis, Deep Face, Machine Learning, Convolution Neural Network, Speech-based Confidence Detection, Librosa, mfcc, confidence evaluator, AI interview.
|
DOI:
10.17148/IJARCCE.2024.134109
