Emotion recognition in conversation
Emotion recognition in conversation (ERC, "emotion recognition in dialogues") is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors. 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). Self- and inter-personal influences play critical role 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, such as, conversational-context modeling, speaker-state modeling, presence of sarcasm in conversation, emotion shift across consecutive utterances of the same interlocutor.
Q1339090
emotion recognition
Concept
Q9415
emotion
Concept
Q131395
dialogue
Concept
Q4425763
interlocutors
Concept
Q202833
social platforms
Concept
Q55008106
multimodal
UNK
Q44619
fear
Concept
Q79871
anger
Concept
Q4425763
interlocutor
Concept
Q96377243
Emotion recognition in conversation
UNK
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