Swansea University
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Funding providers: Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnerships (DTP) and Swansea University’s Faculty of Science and Engineering
Subject areas: Intelligent Robotics and Natural Language Understanding
Project start date:
- 1 October 2024 (Enrolment open from mid-September)
Supervisors:
- Primary supervisor- Dr Julian Hough ([email protected])
- Secondary supervisor- Professor Matt Jones
Aligned programme of study: PhD in Computer Science
Mode of study: Full-time
Project description:
This PhD project will investigate and build spoken language understanding (SLU) models from data for a social care robot simulation, to react quickly and effectively to instructions in a home environment. The models built will respond to instructions like “please put the remote control on the table” and follow-up repairs like “no, the left-hand table” when the speaker realizes the robot has made a mistake, in real time and without delay.
To build these SLU algorithms, the project will involve collecting data with pairs of human participants in a Virtual Reality environment. The models built will aim to give the most accurate user intention word-by-word, but also a continuous measure of confidence corresponding to human reaction times. The models will be tested both in the simulation environment and real-world equivalent robots.
The successful candidate will join the new Intelligent Robotics group in the Computer Science Department in the Computational Foundry in the Faculty of Science and Engineering at Swansea University, in addition to interfacing with the established Human-Computer Interaction (HCI) FIT lab. The candidate will be working alongside other researchers on the FLUIDITY project on human-robot interaction, and those working on other real-world applications.
Eligibility
Candidates must hold an undergraduate degree at 2.1 level in Computer Science; Mathematics; Linguistics or Psychology/Cognitive Science (with evidence of programming and/or NLP/computational linguistics experience), or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University). Evidence of publishable standard projects is also desirable. If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.
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