It improves speakerbased emotion modeling by using memory networks which are efficient in capturing long-term dependencies and summarizing task-specific details using attention models (Weston et al., 2014;Graves et al., 2014;Young et al., 2017).
the memory cells of CMN are continuous vectors that store the context information found in the utterance histories.