Conference item
Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 221.2KB, Terms of use)
-
- Publisher copy:
- 10.1109/ICASSP39728.2021.9413891
Authors
- Publisher:
- IEEE
- Host title:
- ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Pages:
- 7243-7247
- Publication date:
- 2021-05-13
- Acceptance date:
- 2021-01-30
- Event title:
- 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021)
- Event location:
- Toronto, ON, Canada
- Event website:
- https://www.2021.ieeeicassp.org/
- Event start date:
- 2021-06-06
- Event end date:
- 2021-06-11
- DOI:
- EISSN:
-
2379-190X
- ISSN:
-
1520-6149
- EISBN:
- 9781728176055
- ISBN:
- 9781728176062
- Language:
-
English
- Keywords:
- Pubs id:
-
1162376
- Local pid:
-
pubs:1162376
- Deposit date:
-
2021-02-19
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2021
- Rights statement:
- © IEEE 2021.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available from IEEE at: https://doi.org/10.1109/ICASSP39728.2021.9413891
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