Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder
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 mo...
| Main Authors: | , , , , , |
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| Format: | Internet publication |
| Language: | English |
| Published: |
2021
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| _version_ | 1797112964368564224 |
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| author | Wang, B Wu, Y Vaci, N Liakata, M Lyons, T Saunders, KEA |
| author_facet | Wang, B Wu, Y Vaci, N Liakata, M Lyons, T Saunders, KEA |
| author_sort | Wang, B |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-04-09T03:56:26Z |
| format | Internet publication |
| id | oxford-uuid:e2b86ceb-b896-4edb-89fd-9d77fd77ebaa |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-04-09T03:56:26Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | oxford-uuid:e2b86ceb-b896-4edb-89fd-9d77fd77ebaa2024-03-15T13:52:12ZModelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorderInternet publicationhttp://purl.org/coar/resource_type/c_7ad9uuid:e2b86ceb-b896-4edb-89fd-9d77fd77ebaaEnglishSymplectic Elements2021Wang, BWu, YVaci, NLiakata, MLyons, TSaunders, KEABipolar 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. |
| spellingShingle | Wang, B Wu, Y Vaci, N Liakata, M Lyons, T Saunders, KEA Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title | Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title_full | Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title_fullStr | Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title_full_unstemmed | Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title_short | Modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
| title_sort | modelling paralinguistic properties in conversational speech to detect bipolar disorder and borderline personality disorder |
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