Next-Gen AI Interview: Multilingual and Real-Time Analysis

This repository contains my submission for the Twilio Competition.

What is this project about?

The motivation behind this project is to democratize the interview process, making it more accessible, personalized, and fair. Traditional interviews often fail to accommodate individual differences in language proficiency, communication styles, and comfort levels. By leveraging AI and advanced communication technologies, this platform aims to provide an interview experience that not only assesses a candidate's qualifications but also offers real-time support and feedback.

Key Features

• Personalized Interview Setup: Users fill out a survey detailing their job position, experience, skills, goals, and preferred language for the interview.
• Multilingual Support: Interviews can be conducted in the user's preferred language via WhatsApp Business or a web browser.
• AI-Generated Questions and Feedback: Gemini API generates context-specific interview questions and AI-generated feedback.
• Real-Time Body Language Analysis: TensorFlow and PoseNet analyze user posture and eye contact during video interviews.
• Replay and Transcript Features: Users can replay their spoken answers and view live transcripts to improve their performance.
• Seamless Integration with Twilio APIs: Utilizes Twilio WhatsApp Business API, Twilio Voice API, and Twilio Video API for communication channels.

Demo

Tech Stack

• Frontend: React JS
• Backend: Express JS
• Styling: Tailwind CSS
• AI and ML: TensorFlow, PoseNet
• APIs:
  • Twilio APIs (WhatsApp Business, Voice, Video)
  • Gemini API
  • Microsoft Text Translator API

Contributing

Contributions are welcome! Please fork this repository and submit a pull request.

Contact

• Email: muhbil171845@gmail.com
• LinkedIn: LinkedIn Profile