For the emotion classification task we implemented the CNN suggested by the paper. It consists of two convolution layers and 2 fully connected layers followed by a softmax for classification. Each convolution layer is followed by a max pooling layer, normalization and ReLU activation function.

This table contains detailed layers’ configurations. Accuracy of this model was 56% which is much less than the accuracy reported by the paper so we tried modifying the papers network by adding one more convolution layer. We also added some dropouts and ReLUs among the fully connected layers. This increased the accuracy up to 60%.