Available
Project number:
2025_81
Start date:
October 2025
Project themes:
Main supervisor:
Lecturer in AI for Speech Analysis for Healthcare
Co-supervisor:
Dr Ewan Carr
Additional Information:
Utilising responsible artificial intelligence for speech-based assessments of psychological and neurological disorders
Background: Speech is the most complex, rapid function our body performs. In an instant, our brain decides what to say and how to say it and then precisely coordinates over 100 muscles to produce around four syllables per second. There is growing evidence that the rhythm and acoustics of someone’s voice, as well as what they are saying, reveal essential things about their mental and physical health.
Novelty and Importance: This project aims to leverage a responsible AI framework combining speech processing, advanced statistical techniques and artificial intelligence (AI) to provide a comprehensive picture of health-related changes in speech. The applicant will have access to a variety and depth of longitudinal speech data from clinical cohorts that are unique in the field. The findings have the potential to revolutionise our understanding of speech patterns, paving the way for innovative applications in healthcare assessments, personalised therapy plans, cognitive assessment, and beyond.
Aims and Objectives: To develop an analytical framework to characterise and track changes in key symptoms of psychological and neurological disorders using speech markers. The student will learn the signal processing and machine learning techniques required to extract relevant features from RMT-collected speech signals, then assess the suitability of these features for assessing longitudinal changes in speech. This parameterisation will include the incorporation of both knowledge-driven and data-driven approaches, as well as the use of speech and language foundational models. Finally, they will use advanced analytical methods to determine critical temporal dynamics and the evolution of different speech properties in each clinical population.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at