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 …
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …
made it possible to endow machines/computers with the ability of emotion understanding …
Emotion recognition from speech using wav2vec 2.0 embeddings
Emotion recognition datasets are relatively small, making the use of the more sophisticated
deep learning approaches challenging. In this work, we propose a transfer learning method …
deep learning approaches challenging. In this work, we propose a transfer learning method …
Speech emotion recognition with deep convolutional neural networks
The speech emotion recognition (or, classification) is one of the most challenging topics in
data science. In this work, we introduce a new architecture, which extracts mel-frequency …
data science. In this work, we introduce a new architecture, which extracts mel-frequency …
Deep learning for human affect recognition: Insights and new developments
Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
CTNet: Conversational transformer network for emotion recognition
Emotion recognition in conversation is a crucial topic for its widespread applications in the
field of human-computer interactions. Unlike vanilla emotion recognition of individual …
field of human-computer interactions. Unlike vanilla emotion recognition of individual …
Lipopolysaccharide-induced model of neuroinflammation: mechanisms of action, research application and future directions for its use
A Skrzypczak-Wiercioch, K Sałat - Molecules, 2022 - mdpi.com
Despite advances in antimicrobial and anti-inflammatory therapies, inflammation and its
consequences still remain a significant problem in medicine. Acute inflammatory responses …
consequences still remain a significant problem in medicine. Acute inflammatory responses …
Predicting dementia from spontaneous speech using large language models
Language impairment is an important biomarker of neurodegenerative disorders such as
Alzheimer's disease (AD). Artificial intelligence (AI), particularly natural language processing …
Alzheimer's disease (AD). Artificial intelligence (AI), particularly natural language processing …
Automated assessment of psychiatric disorders using speech: A systematic review
Objective There are many barriers to accessing mental health assessments including cost
and stigma. Even when individuals receive professional care, assessments are intermittent …
and stigma. Even when individuals receive professional care, assessments are intermittent …
Alzheimer's dementia recognition through spontaneous speech
The need for inexpensive, safe, accurate and non-invasive biomarkers for Alzheimer's
disease (AD) has motivated much current research (Mandell and Green, 2011). While …
disease (AD) has motivated much current research (Mandell and Green, 2011). While …