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 …
Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …
ageing global population to the current COVID-19 pandemic. In a world where we have …
Conversational emotion recognition studies based on graph convolutional neural networks and a dependent syntactic analysis
Abstract Multimodal Emotion Recognition for Conversation (ERC) is a challenging multi-
class classification task that requires recognizing multiple speakers' emotions in text, audio …
class classification task that requires recognizing multiple speakers' emotions in text, audio …
Transformers in speech processing: A survey
The remarkable success of transformers in the field of natural language processing has
sparked the interest of the speech-processing community, leading to an exploration of their …
sparked the interest of the speech-processing community, leading to an exploration of their …
Revisiting disentanglement and fusion on modality and context in conversational multimodal emotion recognition
It has been a hot research topic to enable machines to understand human emotions in
multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion …
multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion …
Mer 2023: Multi-label learning, modality robustness, and semi-supervised learning
The first Multimodal Emotion Recognition Challenge (MER 2023) 1 was successfully held at
ACM Multimedia. The challenge focuses on system robustness and consists of three distinct …
ACM Multimedia. The challenge focuses on system robustness and consists of three distinct …
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
Robust emotion recognition in context debiasing
Context-aware emotion recognition (CAER) has recently boosted the practical applications
of affective computing techniques in unconstrained environments. Mainstream CAER …
of affective computing techniques in unconstrained environments. Mainstream CAER …
Robust multimodal emotion recognition from conversation with transformer-based crossmodality fusion
Decades of scientific research have been conducted on developing and evaluating methods
for automated emotion recognition. With exponentially growing technology, there is a wide …
for automated emotion recognition. With exponentially growing technology, there is a wide …
DA-Net: Dual-attention network for multivariate time series classification
Multivariate time series classification is one of the increasingly important issues in machine
learning. Existing methods focus on establishing the global long-range dependencies or …
learning. Existing methods focus on establishing the global long-range dependencies or …