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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 176–200 of 202 papers

TitleStatusHype
Variational Fusion for Multimodal Sentiment Analysis—0
Multimodal Transformer for Unaligned Multimodal Language SequencesCode0
Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment AnalysisCode0
Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between ModalitiesCode0
Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal BehaviorsCode0
Learning Robust Joint Representations for Multimodal Sentiment Analysis—0
Multimodal Speech Emotion Recognition Using Audio and TextCode0
Contextual Inter-modal Attention for Multi-modal Sentiment AnalysisCode0
Multimodal Language Analysis with Recurrent Multistage FusionCode0
Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis—0
Polarity and Intensity: the Two Aspects of Sentiment Analysis—0
DNN Multimodal Fusion Techniques for Predicting Video Sentiment—0
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph—0
Multimodal Sentiment Analysis using Hierarchical Fusion with Context ModelingCode0
Efficient Low-rank Multimodal Fusion with Modality-Specific FactorsCode0
Multimodal Sentiment Analysis To Explore the Structure of EmotionsCode0
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines—0
Multi-attention Recurrent Network for Human Communication ComprehensionCode0
Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement LearningCode0
Benchmarking Multimodal Sentiment Analysis—0
Tensor Fusion Network for Multimodal Sentiment AnalysisCode0
Context-Dependent Sentiment Analysis in User-Generated VideosCode0
Select-Additive Learning: Improving Generalization in Multimodal Sentiment AnalysisCode0
Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis—0
10,000+ Times Accelerated Robust Subset Selection (ARSS)—0
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