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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 151–200 of 202 papers

TitleStatusHype
An AutoML-based Approach to Multimodal Image Sentiment Analysis—0
Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment AnalysisCode1
The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements—0
MSAF: Multimodal Split Attention FusionCode1
SWAFN: Sentimental Words Aware Fusion Network for Multimodal Sentiment AnalysisCode1
BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier—0
Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature FusionCode1
MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language SequencesCode1
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment AnalysisCode1
Cross-Modal BERT for Text-Audio Sentiment AnalysisCode1
Modulated Fusion using Transformer for Linguistic-Acoustic Emotion RecognitionCode1
Multimodal Sentiment Analysis with Multi-perspective Fusion Network Focusing on Sense Attentive Language—0
TransModality: An End2End Fusion Method with Transformer for Multimodal Sentiment Analysis—0
Jointly Fine-Tuning “BERT-like” Self Supervised Models to Improve Multimodal Speech Emotion RecognitionCode1
TPFN: Applying Outer Product along Time to Multimodal Sentiment Analysis Fusion on Incomplete Data—0
Multilogue-Net: A Context-Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of ModalityCode1
A Transformer-based joint-encoding for Emotion Recognition and Sentiment AnalysisCode1
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment AnalysisCode1
MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and WorkshopCode1
Gated Mechanism for Attention Based Multimodal Sentiment Analysis—0
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis—0
Multimodal Behavioral Markers Exploring Suicidal Intent in Social Media VideosCode0
Integrating Multimodal Information in Large Pretrained TransformersCode0
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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