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Multimodal Sentiment Analysis

Multimodal sentiment analysis is the task of performing sentiment analysis with multiple data sources - e.g. a camera feed of someone's face and their recorded speech.

( Image credit: ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection )

Papers

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Showing 121–130 of 202 papers

TitleStatusHype
TextMI: Textualize Multimodal Information for Integrating Non-verbal Cues in Pre-trained Language Models—0
Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture—0
Curriculum Learning Meets Weakly Supervised Modality Correlation Learning—0
A Self-Adjusting Fusion Representation Learning Model for Unaligned Text-Audio Sequences—0
On the Use of Modality-Specific Large-Scale Pre-Trained Encoders for Multimodal Sentiment AnalysisCode0
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis—0
Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis—0
Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality—0
AMOA: Global Acoustic Feature Enhanced Modal-Order-Aware Network for Multimodal Sentiment Analysis—0
Modeling Intra- and Inter-Modal Relations: Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis—0
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