Deep learning techniques for speech emotion recognition, from databases to models
The advancements in neural networks and the on-demand need for accurate and near real-
time Speech Emotion Recognition (SER) in human–computer interactions make it …
time Speech Emotion Recognition (SER) in human–computer interactions make it …
[HTML][HTML] Speech emotion recognition using machine learning—A systematic review
Speech emotion recognition (SER) as a Machine Learning (ML) problem continues to
garner a significant amount of research interest, especially in the affective computing …
garner a significant amount of research interest, especially in the affective computing …
Emotalk: Speech-driven emotional disentanglement for 3d face animation
Speech-driven 3D face animation aims to generate realistic facial expressions that match
the speech content and emotion. However, existing methods often neglect emotional facial …
the speech content and emotion. However, existing methods often neglect emotional facial …
Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition
In this paper, a novel approach, which is based on attention guided 3D convolutional neural
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …
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 …
Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques
Speech emotion recognition is one of the challenging research issues in the knowledge-
based system and various methods have been recommended to reach high classification …
based system and various methods have been recommended to reach high classification …
Optimal feature selection based speech emotion recognition using two‐stream deep convolutional neural network
Speech signal processing is an active area of research, the most dominant source of
exchanging information among human beings, and the best way for human–computer …
exchanging information among human beings, and the best way for human–computer …
Variational mode decomposition based acoustic and entropy features for speech emotion recognition
Automated speech emotion recognition (SER) is a machine-based method for identifying
emotion from speech signals. SER has many practical applications, including improving …
emotion from speech signals. SER has many practical applications, including improving …
Negative emotions detection on online mental-health related patients texts using the deep learning with MHA-BCNN model
K Dheeraj, T Ramakrishnudu - Expert Systems with Applications, 2021 - Elsevier
Mining the emotions in the text related to mental health-care oriented is a challenging
aspect, especially dealing with a long-text sequence of data. The extraction of emotions …
aspect, especially dealing with a long-text sequence of data. The extraction of emotions …
Speech emotion recognition using convolution neural networks and multi-head convolutional transformer
Speech emotion recognition (SER) is a challenging task in human–computer interaction
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …