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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 161–170 of 202 papers

TitleStatusHype
Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning—0
Speech-Text Dialog Pre-training for Spoken Dialog Understanding with Explicit Cross-Modal Alignment—0
StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data—0
Stronger Baseline for Robust Results in Multimodal Sentiment Analysis—0
CMSBERT-CLR: Context-driven Modality Shifting BERT with Contrastive Learning for linguistic, visual, acoustic Representations—0
Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysis—0
BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier—0
Targeted aspect based multimodal sentiment analysis:an attention capsule extraction and multi-head fusion network—0
TCAN: Text-oriented Cross Attention Network for Multimodal Sentiment Analysis—0
Benchmarking Multimodal Sentiment Analysis—0
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