Asynchronous Architecture for Real-Time Interview Simulation: A Concurrent Processing Approach to AI-Driven Interviews

DOI

10.2991/978-94-6463-716-8_46How to use a DOI?

Keywords

Interview Automation; Mock Interview Simulation

Abstract

The traditional job interview process faces scalability, availability, and consistency challenges. As a job aspirant in the volatile job market of 2024, I identified the need to create systems that make this process more efficient and consistent for all parties involved, organizations, and candidates. With interview processes varying across companies and job seekers typically submitting hundreds of applications, preparing for each unique interview becomes daunting. Additionally, companies face scalability issues with traditional interviewing processes, where a better understanding of a larger applicant pool could significantly improve their hiring efficiency.

This paper presents an innovative interview bot that addresses the dual challenges of interview readiness and standardized evaluation. The system primarily serves as a practice platform for job aspirants seeking a more quantitative approach to their interview preparation. This platform could also help organizations standardize their interview evaluations by potentially offloading initial candidate screenings to autonomous bots capable of evaluating candidates’ profiles for specific job roles.

By leveraging generative AI technologies, a comprehensive question bank, and a WebRTC framework, this platform simulates realistic interview experiences, improving interview preparedness and evaluations. The realistic simulation is achieved through dynamic question generation, detailed feedback mechanisms, AI-generated voice for natural interaction, and concurrent system design for low-latency output generation. The system incorporates industry-standard evaluation criteria to ensure optimal performance.

The body’s ability to provide consistent, objective feedback while being available 24/7 addresses the limitations of traditional mock interview methods. This research contributes to the evolving landscape of AI-assisted career development tools while offering insights into scalable interview automation solutions.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Parth Bhalerao
PY  - 2025
DA  - 2025/05/26
TI  - Asynchronous Architecture for Real-Time Interview Simulation: A Concurrent Processing Approach to AI-Driven Interviews
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 599
EP  - 610
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_46
DO  - 10.2991/978-94-6463-716-8_46
ID  - Bhalerao2025
ER  -