This internal event is part of our AI and the Arts series. It highlights and maps out expertise and strengths at the intersection of AI / data science and languages / linguistics at the University of Manchester. This highly interdisciplinary area opens several exciting possibilities for research, teaching, knowledge exchange, and business engagement. Researchers from across the University of Manchester’s Digital Futures and Creative Manchester networks spotlight their research in these areas.
Welcome and Context
Digital Futures Creative and Heritage Lead, Dr Kostas Arvanitis, commenced the online event by welcoming attendees, introducing the speakers and giving brief overview of the event objectives here.
Using computational linguistics to detect markers of Parkinson's disease in typing data
The second speaker of the day, Dr Colin Bannard - Senior Lecturer in Linguistics, University of Manchester, described work on using computational linguistics to identify a marker of Parkinson's disease in keystroke recordings from typing. An often-reported early sign of Parkinson's disease is difficulty in performing habitual behaviours. In this work, analysis of samples of a highly automatised behaviour - language use, or specifically typing was carried out. The findings showed a reduction in two key behavioural signatures of habit which can be used to distinguish people with a recent diagnosis of Parkinson's disease from controls. Watch the presentation here.
Computational authorship identification
The first speaker was Dr Andrea Nini - Lecturer in English Language, University of Manchester. In this talk, he gave an overview of modern computational approaches for the identification of anonymous writers, especially for forensic and investigative purposes. He also covered how the application of these techniques is providing new solutions for investigators working on cybercrime on the Dark Web here.