Automated emotion recognition: Current trends and future perspectives
Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …
recognition has applications in multiple domains such as health care, e-learning …
[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …
and modalities using questionnaires, physical signals, and physiological signals. Recently …
Robust speech emotion recognition using CNN+ LSTM based on stochastic fractal search optimization algorithm
One of the main challenges facing the current approaches of speech emotion recognition is
the lack of a dataset large enough to train the currently available deep learning models …
the lack of a dataset large enough to train the currently available deep learning models …
[HTML][HTML] Human-computer interaction with detection of speaker emotions using convolution neural networks
AA Alnuaim, M Zakariah, A Alhadlaq… - Computational …, 2022 - hindawi.com
Emotions play an essential role in human relationships, and many real-time applications rely
on interpreting the speaker's emotion from their words. Speech emotion recognition (SER) …
on interpreting the speaker's emotion from their words. Speech emotion recognition (SER) …
Graph neural architecture search: A survey
In academia and industries, graph neural networks (GNNs) have emerged as a powerful
approach to graph data processing ranging from node classification and link prediction tasks …
approach to graph data processing ranging from node classification and link prediction tasks …
Speech emotion recognition using clustering based GA-optimized feature set
Speech Emotion Recognition (SER) is a hot topic in academia and industry. Feature
engineering plays a pivotal role in building an efficient SER. Although researchers have …
engineering plays a pivotal role in building an efficient SER. Although researchers have …
[HTML][HTML] Emotional speech recognition using deep neural networks
L Trinh Van, T Dao Thi Le, T Le Xuan, E Castelli - Sensors, 2022 - mdpi.com
The expression of emotions in human communication plays a very important role in the
information that needs to be conveyed to the partner. The forms of expression of human …
information that needs to be conveyed to the partner. The forms of expression of human …
A novel spatio-temporal convolutional neural framework for multimodal emotion recognition
Proposing a practical method for high-performance emotion recognition could facilitate
human–computer interaction. Among existing methods, deep learning techniques have …
human–computer interaction. Among existing methods, deep learning techniques have …
An ensemble 1D-CNN-LSTM-GRU model with data augmentation for speech emotion recognition
Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …
Attention-based multi-learning approach for speech emotion recognition with dilated convolution
The success of deep learning in speech emotion recognition has led to its application in
resource-constrained devices. It has been applied in human-to-machine interaction …
resource-constrained devices. It has been applied in human-to-machine interaction …