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Related Papers
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
AbstractThe recognition of emotion and dialogue acts enriches conversational analysis and help to build natural dialogue systems. Emotion interpretation makes us understand feelings and dialogue acts reflect the intentions and …...
MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation
AbstractEmotion recognition in conversation (ERC) is a crucial component in affective dialogue systems, which helps the system understand users’ emotions and generate empathetic responses. However, most works focus on modeling …...
Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities
AbstractFor the missing modality problem in Multimodal Sentiment Analysis (MSA), the inconsistency phenomenon occurs when the sentiment changes due to the absence of a modality. The absent modality that determines …...
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition
AbstractMultimodal sentiment analysis (MSA) and emotion recognition in conversation (ERC) are key research topics for computers to understand human behaviors. From a psychological perspective, emotions are the expression of affect …...
Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression
AbstractIn automatic emotion recognition (AER), labels assigned by different human annotators to the same utterance are often inconsistent due to the inherent complexity of emotion and the subjectivity of perception. …...