Before revision:  In the experimental results, two datasets are used: RECOLA for continuous dimensional emotion recognition and DAIC-WOZ for automatic depression diagnosis. The extensive experiments showed that the proposed approach significantly outperforms previous works in the literature in both datasets .
After revision:  Our model outperforms the state-of-the-art methods for RECOLA and for DAIC-WOZ datasets and it reaches high accuracies of 89.30\%, 91.44\% and 73.25\% in predicting arousal, valence, and depression, respectively .