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Emotion recognition in conversations is an important step in various virtualchat bots which require opinion-based feedback, like in social media threads,online support and many more applications. Current Emotion recognition inconversations models face issues like (a) loss of contextual information inbetween two dialogues of a conversation, (b) failure to give appropriateimportance to significant tokens in each utterance and (c) inability to pass onthe emotional information from previous utterances.The proposed model ofAdvanced Contextual Feature Extraction (AdCOFE) addresses these issues byperforming unique feature extraction using knowledge graphs, sentiment lexiconsand phrases of natural language at all levels (word and position embedding) ofthe utterances. Experiments on the Emotion recognition in conversations datasetshow that AdCOFE is beneficial in capturing emotions in conversations.

AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification