School of Science and Technology 科技學院
Computing Programmes 電腦學系
| Programme | Bachelor of Computing with Honours in Internet Technology Bachelor of Science with Honours in Computer Science |
| Supervisor | Dr. Keith Lee |
| Areas | Virtual Reality Applications |
| Year of Completion | 2024 |
This report presents a VR prototype called Job Interview Simulator as a solution to reinforce better performance in first job interviews taken by fresh graduates.
The project aims to support fresh graduates in improving their job interview performance through a VR-based application. The key goals include:
The system is designed to provide feedback and track user progress, enhancing both language skills and interview readiness.
Demonstration Video
Presentation Video
Our solution leveraged existing hardware but innovated in software aspects, including backend scripts and user-facing programs.
The project has entered its final development phase using PICO 4 Pro VR headsets. Key components include:
VR Application Development:
Server-Side Processing:
Sample Q&A Module:
Chatbot Interviewer:
Voice Interaction:
Use Case Diagram and Function List:
There is only one user type in our application which is the user themselves. The user would first choose a VR scene and a question type before starting their job interview practice. They would be able to practice their interview responses in three different ways including picking a choice in multiple-choice questions, reading aloud a suggested answer, and answering questions in their own words. The details are shown as follows
Figure 1: Use Case Diagram and Function List
Figure 2: Application Hierarchy
Figure 3: Design Chart of Sample Q&A/Pronunciation Training
Once a VR user opens the Q&A module to start learning, Unity can visit the Python server by accessing a URL link. The Python server will be acknowledged to call one of its functions to collect all data stored in a JSON file. As mentioned before, the JSON file is deployed to store and update all questions, answers and explanations. The Python server then relays the data back to Unity so that VR user can see the questions, answers and explanations one by one.
Figure 4: JSON file for the Q&A Reading module
The system enables real-time pronunciation feedback in the VR interview app using a multi-layered architecture:
This setup combines cloud storage, real-time processing, and speech analytics to deliver detailed and automated feedback on spoken performance.
Figure 5: Design Chart of Speech Scoring System
3D models
Figure 6: Office Meeting Room Scene (Unity 3D)
Figure 7: Office Reception Area Scene (Unity 3D)
Question and Answer Reading
This module helps users improve speaking and presentation skills by allowing them to practice reading aloud sample job interview questions and answers, followed by detailed speech performance analysis.
Key Features:
Language Options: Users can choose to practice in English, Cantonese, or Mandarin, with the system adjusting accordingly.
Figure 8
Interactive Q&A: Users can view sample questions, answers, and explanations on a virtual panel and navigate through different Q&A sets.
Figure 9
Users record their spoken responses using a VR interface.
Figure 10
A color-coded word accuracy list helps identify specific pronunciation errors (green = excellent, red = poor).
Figure 11
Module- Virtual Interview
The module blends interactivity, real-time feedback, and multilingual support to enhance users' job interview readiness and spoken language proficiency
Key Features:
Start Interface: Users begin the session by clicking “Start” to enter the interview scene.
Figure 12
Language Options: Users can choose between English, Cantonese, or Mandarin before proceeding.
Figure 13
A microphone button appears after language selection.
Users record their responses by clicking the mic; input is disabled while speaking.
Figure 14
After recording, users can view their spoken text, delete it, or resend it.
Figure 15
Clicking “Send” transmits the response via ZMQ to a backend server.
Figure 16
The POE chatbot processes user input and returns a reply.
Figure 17
The response is converted to speech for playback.
Users can click “Replay” to hear the interviewer's response again.
Figure 18
If users do not look at the interviewer, “Look at the interviewer!” will appear to remind users.
Figure 19
Key Achievements
Limitations
Jonathan handles all external affairs include business development, patents write up and public relations. He is frequently interviewed by media and is considered a pioneer in 3D printing products.
After graduating from OUHK, Krutz obtained an M.Sc. in Engineering Management from CityU. He is now completing his second master degree, M.Sc. in Biomedical Engineering, at CUHK. Krutz has a wide range of working experience. He has been with Siemens, VTech, and PCCW.
Hugo Leung Wai-yin, who graduated from his four-year programme in 2015, won the Best Paper Award for his ‘intelligent pill-dispenser’ design at the Institute of Electrical and Electronics Engineering’s International Conference on Consumer Electronics – China 2015.
The pill-dispenser alerts patients via sound and LED flashes to pre-set dosage and time intervals. Unlike units currently on the market, Hugo’s design connects to any mobile phone globally. In explaining how it works, he said: ‘There are three layers in the portable pillbox. The lowest level is a controller with various devices which can be connected to mobile phones in remote locations. Patients are alerted by a sound alarm and flashes. Should they fail to follow their prescribed regime, data can be sent via SMS to relatives and friends for follow up.’ The pill-dispenser has four medicine slots, plus a back-up with a LED alert, topped by a 500ml water bottle. It took Hugo three months of research and coding to complete his design, but he feels it was worth all his time and effort.
Hugo’s public examination results were disappointing and he was at a loss about his future before enrolling at the OUHK, which he now realizes was a major turning point in his life. He is grateful for the OUHK’s learning environment, its industry links and the positive guidance and encouragement from his teachers. The University is now exploring the commercial potential of his design with a pharmaceutical company. He hopes that this will benefit the elderly and chronically ill, as well as the society at large.
Soon after completing his studies, Hugo joined an automation technology company as an assistant engineer. He is responsible for the design and development of automation devices. The target is to minimize human labor and increase the quality of products. He is developing products which are used in various sections, including healthcare, manufacturing and consumer electronics.
| Course Code | Title | Credits | |
|---|---|---|---|
| COMP S321F | Advanced Database and Data Warehousing | 5 | |
| COMP S333F | Advanced Programming and AI Algorithms | 5 | |
| COMP S351F | Software Project Management | 5 | |
| COMP S362F | Concurrent and Network Programming | 5 | |
| COMP S363F | Distributed Systems and Parallel Computing | 5 | |
| COMP S382F | Data Mining and Analytics | 5 | |
| COMP S390F | Creative Programming for Games | 5 | |
| COMP S492F | Machine Learning | 5 | |
| ELEC S305F | Computer Networking | 5 | |
| ELEC S348F | IOT Security | 5 | |
| ELEC S371F | Digital Forensics | 5 | |
| ELEC S431F | Blockchain Technologies | 5 | |
| ELEC S425F | Computer and Network Security | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| ELEC S201F | Basic Electronics | 5 | |
| IT S290F | Human Computer Interaction & User Experience Design | 5 | |
| STAT S251F | Statistical Data Analysis | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| COMPS333F | Advanced Programming and AI Algorithms | 5 | |
| COMPS362F | Concurrent and Network Programming | 5 | |
| COMPS363F | Distributed Systems and Parallel Computing | 5 | |
| COMPS380F | Web Applications: Design and Development | 5 | |
| COMPS381F | Server-side Technologies and Cloud Computing | 5 | |
| COMPS382F | Data Mining and Analytics | 5 | |
| COMPS390F | Creative Programming for Games | 5 | |
| COMPS413F | Application Design and Development for Mobile Devices | 5 | |
| COMPS492F | Machine Learning | 5 | |
| ELECS305F | Computer Networking | 5 | |
| ELECS363F | Advanced Computer Design | 5 | |
| ELECS425F | Computer and Network Security | 5 |
