Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions
Sentiment analysis (SA) has gained much traction In the field of artificial intelligence (AI) and
natural language processing (NLP). There is growing demand to automate analysis of user …
natural language processing (NLP). There is growing demand to automate analysis of user …
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
S Zhang, Y Yang, C Chen, X Zhang, Q Leng… - Expert Systems with …, 2024 - Elsevier
Emotion recognition has recently attracted extensive interest due to its significant
applications to human–computer interaction. The expression of human emotion depends on …
applications to human–computer interaction. The expression of human emotion depends on …
Multimodal sentiment analysis based on fusion methods: A survey
Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …
an entity. It can be applied in a variety of different fields and scenarios, such as product …
Learning modality-specific representations with self-supervised multi-task learning for multimodal sentiment analysis
Abstract Representation Learning is a significant and challenging task in multimodal
learning. Effective modality representations should contain two parts of characteristics: the …
learning. Effective modality representations should contain two parts of characteristics: the …
State of the art: a review of sentiment analysis based on sequential transfer learning
Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …
A multitask learning model for multimodal sarcasm, sentiment and emotion recognition in conversations
Sarcasm, sentiment and emotion are tightly coupled with each other in that one helps the
understanding of another, which makes the joint recognition of sarcasm, sentiment and …
understanding of another, which makes the joint recognition of sarcasm, sentiment and …
Multimodal video sentiment analysis using deep learning approaches, a survey
Deep learning has emerged as a powerful machine learning technique to employ in
multimodal sentiment analysis tasks. In the recent years, many deep learning models and …
multimodal sentiment analysis tasks. In the recent years, many deep learning models and …
Multimodal Emotion Recognition with deep learning: advancements, challenges, and future directions
In recent years, affective computing has become a topic of considerable interest, driven by
its ability to enhance several domains, such as mental health monitoring, human–computer …
its ability to enhance several domains, such as mental health monitoring, human–computer …
Transformer-based feature reconstruction network for robust multimodal sentiment analysis
Improving robustness against data missing has become one of the core challenges in
Multimodal Sentiment Analysis (MSA), which aims to judge speaker sentiments from the …
Multimodal Sentiment Analysis (MSA), which aims to judge speaker sentiments from the …
Efficient multimodal transformer with dual-level feature restoration for robust multimodal sentiment analysis
With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA)
has attracted increasing attention recently. Despite significant progress, there are still two …
has attracted increasing attention recently. Despite significant progress, there are still two …