Documentation for AI-Based Interview System

Documentation for AI-Based Interview System

Introduction

This document outlines the implementation and functionalities of an AI-based interview system. The system uses voice technology to ask candidates questions, records their responses, transcribes the audio using a transcription model, and evaluates the answers using a large language model (LLM). This platform provides an efficient, scalable, and consistent solution for conducting interviews.

Purpose of the AI-Based Interview System

The primary objectives of this system are:

  1. Automation: Streamline the interview process by leveraging AI technologies.
  2. Consistency: Ensure uniform evaluation criteria across all candidates.
  3. Scalability: Handle large volumes of interviews without human intervention.
  4. Insights: Provide detailed feedback and analytics on candidate performance.
Video Thumbnail

System Overview

The AI-based interview system consists of the following core components:

  1. Containerized Environments: Each lab instance runs in a container, ensuring isolation and security.
  2. Preconfigured Services: Includes pre-deployed services and tools relevant to cybersecurity demonstrations.
  3. Web-Based Access: Labs are accessible via a browser, ensuring platform independence.
  4. Scalable Deployment: Can accommodate multiple concurrent users.
Key Features
  • Voice-based interaction for a natural interview experience.
  • Advanced transcription for accurate text conversion.
  • AI-powered evaluation for objective and insightful assessments.
  • Configurable question sets tailored to specific roles or industries.

Workflow

  1. Interview Initialization
    • Input: Candidate details and interview configuration (question set, duration, etc.).
    • Process: System prepares the interview environment, including voice synthesis setup and recording parameters.
  2. Question Delivery
    • The system uses a custom-trained text-to-speech (TTS) model to pose questions to the candidate.
    • Questions are Pre-defined, From a pre-configured list.
  3. Response Recording
    • The system records the candidate’s answers in audio format.
    • Ensures high fidelity for accurate transcription.
  4. Audio Transcription
    • The recorded audio is passed to a custom transcription model.
    • Produces a detailed and accurate text transcript of the candidate’s responses.
  5. Answer Evaluation
    • The transcription text is processed by the Gemini API for evaluation.
    • The evaluation includes:
      1. Content analysis: Checks the relevance, accuracy, and depth of answers.
      2. Language proficiency: Assesses grammar, vocabulary, and fluency.