Emotion_recognition_in_conversation
Emotion recognition in conversation (ERC) is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors.[1] The datasets in this field are usually derived from social platforms that allow free and plenty of samples, often containing multimodal data (i.e., some combination of textual, visual, and acoustic data).[2] Self- and inter-personal influences play critical role[3] in identifying some basic emotions, such as, fear, anger, joy, surprise, etc. The more fine grained the emotion labels are the harder it is to detect the correct emotion. ERC poses a number of challenges,[1] such as, conversational-context modeling, speaker-state modeling, presence of sarcasm in conversation, emotion shift across consecutive utterances of the same interlocutor.