Mathematical analysis

Psychology

Programming language

Communication

Artificial intelligence

Geometry

Conversation

Utterance

Mathematics

Domain (mathematical analysis)

Geography

Emotion recognition

Human–computer interaction

Computer science

Geodesy

Orientation (vector space)

Benchmark (surveying)

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Natural language processing

Emotion detection

Emotion recognition in conversations is crucial for building empathetic machines. Present works in this domain do not explicitly consider the inter-personal influences that thrive in the emotional dynamics of dialogues. To this end, we propose Interactive COnversational memory Network (ICON), a multimodal emotion detection framework that extracts multimodal features from conversational videos and hierarchically models the self- and inter-speaker emotional influences into global memories. Such memories generate contextual summaries which aid in predicting the emotional orientation of utterance-videos. Our model outperforms state-of-the-art networks on multiple classification and regression tasks in two benchmark datasets.

ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection