| Paper ID | SPE-56.1 |
| Paper Title |
Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder |
| Authors |
Bo Wang, Yue Wu, University of Oxford, United Kingdom; Nemanja Vaci, University of Sheffield, United Kingdom; Maria Liakata, Queen Mary University of London, United Kingdom; Terry Lyons, Kate Saunders, University of Oxford, United Kingdom |
| Session | SPE-56: Paralinguistics in Speech |
| Location | Gather.Town |
| Session Time: | Friday, 11 June, 14:00 - 14:45 |
| Presentation Time: | Friday, 11 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Speech Processing: [SPE-ANLS] Speech Analysis |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Bipolar disorder (BD) and borderline personality disorder (BPD) are two chronic mental health conditions the clinicians find challenging to distinguish based on clinical interviews, due to their overlapping symptoms. In this work, we investigate the automatic detection of the two conditions by modelling both verbal and non-verbal cues in a set of interviews. We propose a new approach of modelling short-term features with visibility-signature transform, and compare with widely used high-level statistical functions. We demonstrate the superior performance of our proposed signature-based model. Furthermore, we show the role of different sets of features in characterising BD and BPD. |
