Papers with multi-modal sentiment and emotion analysis
Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis (N19-1)
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Md Shad Akhtar, Dushyant Chauhan, Deepanway Ghosal, Soujanya Poria, Asif Ekbal, Pushpak Bhattacharyya
| Challenge: | Existing frameworks for sentiment and emotion analysis are not efficient for inter-task learning. |
| Approach: | They propose a multi-task learning framework that performs sentiment and emotion analysis together. |
| Outcome: | The proposed framework improves on a CMU-MOSEI dataset for sentiment and emotion analysis. |
Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis (D19-1)
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| Challenge: | Multi-modal analysis is a field emerging in the fields of natural language processing, computer vision and speech processing . multimodal analysis uses a variety of information from multiple sources to build efficient systems . acoustic and visual information can provide better information for classification decisions . |
| Approach: | They propose a recurrent neural network based approach for multi-modal sentiment and emotion analysis . they employ a context-aware attention module to exploit the correspondence among neighboring utterances . |
| Outcome: | The proposed model learns inter-modal interaction among participating modalities through auto-encoder mechanism . it is compared with existing state-of-the-art models on five standard multi-modal affect analysis datasets . |