Wang, B., Wu, Y., Vaci, N. orcid.org/0000-0002-8094-0902 et al. (3 more authors) (2021) Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder. In: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing, 06-11 Jun 2021, Toronto, Ontario, Canada. Institute of Electrical and Electronics Engineers , pp. 7243-7247. ISBN 9781728176062
Abstract
Bipolar disorder (BD) and borderline personality disorder (BPD) are two chronic mental health conditions that clinicians find challenging to distinguish based on clinical interviews, due to their overlapping symptoms. In this work, we investigate the automatic detection of these 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 it 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.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | bipolar disorder; borderline personality disorder; speech analysis; paralinguistic modelling; path signature |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Feb 2022 11:48 |
Last Modified: | 13 May 2022 00:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/icassp39728.2021.9413891 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183330 |