  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.
