Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos

NAACL 2018 Devamanyu HazarikaSoujanya PoriaAmir ZadehErik CambriaLouis-Philippe MorencyRoger Zimmermann

Emotion recognition in conversations is crucial for the development of empathetic machines. Present methods mostly ignore the role of inter-speaker dependency relations while classifying emotions in conversations... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Emotion Recognition in Conversation IEMOCAP CMN F1 56.13 # 9
Emotion Recognition in Conversation SEMAINE CMN MAE (Valence) 0.192 # 5
MAE (Arousal) 0.213 # 4
MAE (Expectancy) 0.195 # 5
MAE (Power) 8.74 # 5

Methods used in the Paper