Automated Analysis of Clinical Interviews Using Language and Speech Processing

This Joint PhD project, 'Automated Analysis of Clinical Interviews Using Language and Speech Processing,' is offered by the School of Computer Science at the University of Birmingham, with a collaborative component at the University of Melbourne. The research focuses on improving the understanding and assessment of talking therapies, which are widely used for mental health and behavioural problems. Despite their popularity and effectiveness, the mechanisms behind talking therapies remain unclear, and current quality assurance methods rely heavily on human assessors, making them costly and difficult to scale. The project aims to develop automated methods for analysing clinical interviews using advanced techniques in language analysis, speech analysis, and large language models. By investigating whether automatic analysis can match the effectiveness of human assessment and exploring the underlying mechanisms of talking therapy, the research seeks to enhance therapist training and improve patient outcomes. The work will be conducted in close collaboration with clinicians, integrating expertise from speech processing, natural language processing, and machine learning. Students will benefit from a dynamic research environment, access to state-of-the-art computational resources, and the opportunity to spend at least 12 months at the University of Melbourne. The project is funded by the Priestley Scholarship, which covers tuition and provides a stipend. Applicants should have a strong academic background in Computer Science, Linguistics, Psychology, or related fields, and demonstrate interest or experience in NLP, speech analysis, or machine learning. Good communication skills and the ability to work collaboratively are essential. International candidates may need to meet English language requirements. The application deadline is March 31, 2026. Interested candidates should apply online through the University of Birmingham portal, preparing a CV, academic transcripts, and a statement of research interest. For further details and to access the application, visit the project link provided.