27 March 2023
About the research project
Soldiers can be located in extreme environment and hazardous situations, and using VR associated with the conversation proves an extremely efficient way to train soldiers among various situations and environment, such as flight simulations, battlefield simulations, job training and etc.
At present, most conversations embedded in virtual reality are typically structured interaction. This would allow conversations to take place and would be the normal method of communication. This form of conversation representation is restrictive, allowing for only a few predetermined responses to performing a few simple tasks. We can generalise these limitations in two prime categories, lacks adaptive and dynamic conversation content and a significant lack of relationships between conversational interface and knowledge.
These limitations provide an opportunity which motivates us to develop the next generation of conversation engine that is a cohesive unit of intelligent CLT (Control Language Interface) with assisted rule-based technology and adaptability at its core. The design of this conversation engine is intended to effectively identify the required knowledge for the soldiers while interacting and develop a broader range of contents with an agile delivery mechanism that can cater a wider scope defense situations and environment. We propose our approach that specifically addresses the above-mentioned limitations by targeting the following:
- Identification of the missing/required knowledge of soldiers during VR military training to achieve personalised training
- Generation of interactive conversations based on multiple VR situations and environment
In our system, the interactive conversations will be dynamically changed and adaptive to various VR situations and environment. This unique and novel concept will enable the soldiers to invoke live knowledge generation during training as he/she explores additional information with experiences. Moreover, it will enhance and expand the core knowledge engine, by a wider range of contexts and their inter-matching connectivity to establish conversational flow in various domains of knowledge.
Primary SupervisorMeet Prof Byeong Kang
Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:
- a living allowance stipend of $31,500 per annum (2023 rate, indexed annually) for 3.5 years
- a relocation allowance of up to $2,000
- a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)
If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.
As part of the application process you may indicate if you do not wish to be considered for scholarship funding.
Applicants should review the Higher Degree by Research minimum entry requirements.
Applicants from the following discipline are encouraged to apply:
- ICT discipline (Honours or Equivalent) background
The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.
Additional essential selection criteria specific to this project:
- Undergraduate AI unit(s)
Additional desirable selection criteria specific to this project:
- VR/AR or Project experience in AI
There is a three-step application process:
- Select your project, and check you meet the eligibility and selection criteria;
- Contact the Primary Supervisor, Prof Byeong Kang to discuss your suitability and the project's requirements; and
- Submit an application by the closing date listed above.
- Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
- As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.
Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.
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