[HTML][HTML] An ongoing review of speech emotion recognition
User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …
Clustering-based speech emotion recognition by incorporating learned features and deep BiLSTM
Emotional state recognition of a speaker is a difficult task for machine learning algorithms
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
AAD-Net: Advanced end-to-end signal processing system for human emotion detection & recognition using attention-based deep echo state network
Speech signals are the most convenient way of communication between human beings and
the eventual method of Human–Computer Interaction (HCI) to exchange emotions and …
the eventual method of Human–Computer Interaction (HCI) to exchange emotions and …
Att-Net: Enhanced emotion recognition system using lightweight self-attention module
S Kwon - Applied Soft Computing, 2021 - Elsevier
Speech emotion recognition (SER) is an active research field of digital signal processing
and plays a crucial role in numerous applications of Human–computer interaction (HCI) …
and plays a crucial role in numerous applications of Human–computer interaction (HCI) …
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 …
Human‐Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks
AA Alnuaim, M Zakariah, A Alhadlaq… - Computational …, 2022 - Wiley Online Library
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 …
rely on interpreting the speaker's emotion from their words. Speech emotion recognition …
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 …
CLSTM: Deep feature-based speech emotion recognition using the hierarchical ConvLSTM network
Artificial intelligence, deep learning, and machine learning are dominant sources to use in
order to make a system smarter. Nowadays, the smart speech emotion recognition (SER) …
order to make a system smarter. Nowadays, the smart speech emotion recognition (SER) …
Speech emotion recognition with deep learning
This paper proposes an emotion recognition system based on speech signals in two-stage
approach, namely feature extraction and classification engine. Firstly, two sets of feature are …
approach, namely feature extraction and classification engine. Firstly, two sets of feature are …