Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
Table 3: Final results on the test datasets of EmoryNLP, MELD.
['Method', 'EmoryNLP', 'MELD']
We can see that all our baseline results are strong and can achieve comparable performance with the previous state-of-the-art systems. The best-reported numbers on the EmoryNLP and MELD datasets are 34.39% and 59.40%, respectively. Our BERT-based baseline gives F-scores of 34.76% and 61.31%, respectively, which are both higher than the previous state-of-the-arts.