Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews

Bo Wang, Yue Wu, Niall Taylor, Terry Lyons, Maria Liakata, Alejo J. Nevado-Holgado, Kate E.A. Saunders


Bipolar disorder (BD) and borderline personality disorder (BPD) are both chronic psychiatric disorders. However, their overlapping symptoms and common comorbidity make it challenging for the clinicians to distinguish the two conditions on the basis of a clinical interview. In this work, we first present a new multi-modal dataset containing interviews involving individuals with BD or BPD being interviewed about a non-clinical topic . We investigate the automatic detection of the two conditions, and demonstrate a good linear classifier that can be learnt using a down-selected set of features from the different aspects of the interviews and a novel approach of summarising these features. Finally, we find that different sets of features characterise BD and BPD, thus providing insights into the difference between the automatic screening of the two conditions.


 DOI: 10.21437/Interspeech.2020-3040

Cite as: Wang, B., Wu, Y., Taylor, N., Lyons, T., Liakata, M., Nevado-Holgado, A.J., Saunders, K.E. (2020) Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews. Proc. Interspeech 2020, 437-441, DOI: 10.21437/Interspeech.2020-3040.


@inproceedings{Wang2020,
  author={Bo Wang and Yue Wu and Niall Taylor and Terry Lyons and Maria Liakata and Alejo J. Nevado-Holgado and Kate E.A. Saunders},
  title={{Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews}},
  year=2020,
  booktitle={Proc. Interspeech 2020},
  pages={437--441},
  doi={10.21437/Interspeech.2020-3040},
  url={http://dx.doi.org/10.21437/Interspeech.2020-3040}
}