  In this paper, we present our solution to the MuSe-Humor sub-challenge of the
Multimodal Emotional Challenge (MuSe) 2022. The goal of the MuSe-Humor
sub-challenge is to detect humor and calculate AUC from audiovisual recordings
of German football Bundesliga press conferences. It is annotated for humor
displayed by the coaches. For this sub-challenge, we first build a discriminant
model using the transformer module and BiLSTM module, and then propose a hybrid
fusion strategy to use the prediction results of each modality to improve the
performance of the model. Our experiments demonstrate the effectiveness of our
proposed model and hybrid fusion strategy on multimodal fusion, and the AUC of
our proposed model on the test set is 0.8972.
