A systematic review on multimodal emotion recognition: building blocks, current state, applications, and challenges
Emotion recognition involves accurately interpreting human emotions from various sources
and modalities, including questionnaires, verbal, and physiological signals. With its broad …
and modalities, including questionnaires, verbal, and physiological signals. With its broad …
[HTML][HTML] Emotion fusion for mental illness detection from social media: A survey
Mental illnesses are one of the most prevalent public health problems worldwide, which
negatively influence people's lives and society's health. With the increasing popularity of …
negatively influence people's lives and society's health. With the increasing popularity of …
Towards multimodal sentiment analysis debiasing via bias purification
Abstract Multimodal Sentiment Analysis (MSA) aims to understand human intentions by
integrating emotion-related clues from diverse modalities, such as visual, language, and …
integrating emotion-related clues from diverse modalities, such as visual, language, and …
Towards robust multimodal sentiment analysis under uncertain signal missing
Multimodal Sentiment Analysis (MSA) has attracted widespread research attention recently.
Most MSA studies are based on the assumption of signal completeness. However, many …
Most MSA studies are based on the assumption of signal completeness. However, many …
Multimodal sensing for depression risk detection: integrating audio, video, and text data
Depression is a major psychological disorder with a growing impact worldwide. Traditional
methods for detecting the risk of depression, predominantly reliant on psychiatric …
methods for detecting the risk of depression, predominantly reliant on psychiatric …
General debiasing for multimodal sentiment analysis
Existing work on Multimodal Sentiment Analysis (MSA) utilizes multimodal information for
prediction yet unavoidably suffers from fitting the spurious correlations between multimodal …
prediction yet unavoidably suffers from fitting the spurious correlations between multimodal …
IIFDD: Intra and inter-modal fusion for depression detection with multi-modal information from Internet of Medical Things
Depression is now a prevalent mental illness and multimodal data-based depression
detection is an essential topic of research. Internet of Medical Things devices can provide …
detection is an essential topic of research. Internet of Medical Things devices can provide …
Coordinated-joint translation fusion framework with sentiment-interactive graph convolutional networks for multimodal sentiment analysis
Interactive fusion methods have been successfully applied to multimodal sentiment analysis,
due to their ability to achieve data complementarity via interaction of different modalities …
due to their ability to achieve data complementarity via interaction of different modalities …
A feature-based restoration dynamic interaction network for multimodal sentiment analysis
Multimodal sentiment analysis aims to infer the sentiment of video bloggers from the features
of multiple input modalities. However, there are problems such as signal noise and signal …
of multiple input modalities. However, there are problems such as signal noise and signal …
Multimodal mutual attention-based sentiment analysis framework adapted to complicated contexts
L He, Z Wang, L Wang, F Li - … on Circuits and Systems for Video …, 2023 - ieeexplore.ieee.org
Sentiment analysis has broad application prospects in the field of social opinion mining. The
openness and invisibility of the internet makes users' expression styles more diverse and …
openness and invisibility of the internet makes users' expression styles more diverse and …