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 …
A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
Hybrid contrastive learning of tri-modal representation for multimodal sentiment analysis
The wide application of smart devices enables the availability of multimodal data, which can
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
Sentiment analysis and topic recognition in video transcriptions
Nowadays, videos are an integral modality for information sharing on the World Wide Web.
However, systems able to automatically understand the content and sentiment of a video are …
However, systems able to automatically understand the content and sentiment of a video are …
Authorship identification using ensemble learning
With time, textual data is proliferating, primarily through the publications of articles. With this
rapid increase in textual data, anonymous content is also increasing. Researchers are …
rapid increase in textual data, anonymous content is also increasing. Researchers are …
The MuSe 2021 multimodal sentiment analysis challenge: sentiment, emotion, physiological-emotion, and stress
Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
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 …
The muse 2022 multimodal sentiment analysis challenge: humor, emotional reactions, and stress
The Multimodal Sentiment Analysis Challenge (MuSe) 2022 is dedicated to multimodal
sentiment and emotion recognition. For this year's challenge, we feature three datasets:(i) …
sentiment and emotion recognition. For this year's challenge, we feature three datasets:(i) …
MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox
We introduce the MuSe-Toolbox-a Python-based open-source toolkit for creating a variety of
continuous and discrete emotion gold standards. In a single framework, we unify a wide …
continuous and discrete emotion gold standards. In a single framework, we unify a wide …