Speech Analysis for Automatic Mania Assessment in Bipolar Disorder

Pınar Baki; Heysem Kaya; Elvan Çiftçi; Hüseyin Güleç; Albert Ali Salah

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arXiv · 2202.06766

Speech Analysis for Automatic Mania Assessment in Bipolar Disorder

Pınar Baki·Heysem Kaya·Elvan Çiftçi·Hüseyin Güleç·Albert Ali Salah

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Abstract

Bipolar disorder is a mental disorder that causes periods of manic and depressive episodes. In this work, we classify recordings from Bipolar Disorder corpus that contain 7 different tasks, into hypomania, mania, and remission classes using only speech features. We perform our experiments on splitted tasks from the interviews. Best results achieved on the model trained with 6th and 7th tasks together gives 0.53 UAR (unweighted average recall) result which is higher than the baseline results of the corpus.

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Pınar Baki, Heysem Kaya, Elvan Çiftçi, Hüseyin Güleç, Albert Ali Salah. 2022-02-05. Speech Analysis for Automatic Mania Assessment in Bipolar Disorder. https://arxiv.org/abs/2202.06766

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