Multi-attention Recurrent Network for Human Communication Comprehension
Table 4: Emotion recognition results on IEMOCAP test set using multimodal methods. Our model outperforms the previous baselines and the best scores are highlighted in bold.
['Task', 'Emotions', 'Emotions', 'Valence', 'Valence', 'Arousal', 'Arousal', 'Dominance', 'Dominance']
Our approach achieves state-of-the-art performance in emotion recognition: both emotion classification as well as continuous emotion regression except for the case of correlation in dominance which our results are competitive but not state of the art.