Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
Table 2: Ablated performance on EmoryNLP and MELD, where IUE and CUE denote individual and contextual utterance encoders, respectively.
['Interaction Mode IUE', 'Interaction Mode CUE', 'EmoryNLP', 'MELD']
To comprehensively study the effectiveness of the two bridging neural network structures at the different levels for mutual interaction, we conduct ablation experiments in detail. We can see that both the two networks can bring improved performance for CER. By excluding the bridging network at IUE, our final model falls by 0.19% on EmoryNLP and 0.50% on MELD, respectively. Similarly, the model shows 0.45% and 0.80% declines on the two datasets by eliminating the bridging network at CUE, respectively. When both network structures are removed, drops by 0.72% and 1.43% points on the two datasets are resulted, respectively.