A review on speech emotion recognition using deep learning and attention mechanism
Emotions are an integral part of human interactions and are significant factors in determining
user satisfaction or customer opinion. speech emotion recognition (SER) modules also play …
user satisfaction or customer opinion. speech emotion recognition (SER) modules also play …
Deep representation learning in speech processing: Challenges, recent advances, and future trends
Research on speech processing has traditionally considered the task of designing hand-
engineered acoustic features (feature engineering) as a separate distinct problem from the …
engineered acoustic features (feature engineering) as a separate distinct problem from the …
A novel deep learning framework for state of health estimation of lithium-ion battery
Y Fan, F **ao, C Li, G Yang, X Tang - Journal of Energy Storage, 2020 - Elsevier
The state-of-health (SOH) estimation is a challenging task for lithium-ion battery, which
contribute significantly to maximize the performance of battery-powered systems and guide …
contribute significantly to maximize the performance of battery-powered systems and guide …
Speech emotion recognition from 3D log-mel spectrograms with deep learning network
H Meng, T Yan, F Yuan, H Wei - IEEE access, 2019 - ieeexplore.ieee.org
Speech emotion recognition is a vital and challenging task that the feature extraction plays a
significant role in the SER performance. With the development of deep learning, we put our …
significant role in the SER performance. With the development of deep learning, we put our …
Speech emotion recognition using recurrent neural networks with directional self-attention
As an important branch of affective computing, Speech Emotion Recognition (SER) plays a
vital role in human–computer interaction. In order to mine the relevance of signals in audios …
vital role in human–computer interaction. In order to mine the relevance of signals in audios …
Impact of feature selection algorithm on speech emotion recognition using deep convolutional neural network
Speech emotion recognition (SER) plays a significant role in human–machine interaction.
Emotion recognition from speech and its precise classification is a challenging task because …
Emotion recognition from speech and its precise classification is a challenging task because …
Temporal modeling matters: A novel temporal emotional modeling approach for speech emotion recognition
Speech emotion recognition (SER) plays a vital role in improving the interactions between
humans and machines by inferring human emotion and affective states from speech signals …
humans and machines by inferring human emotion and affective states from speech signals …
[HTML][HTML] Speech emotion recognition using fusion of three multi-task learning-based classifiers: HSF-DNN, MS-CNN and LLD-RNN
Speech emotion recognition plays an increasingly important role in emotional computing
and is still a challenging task due to its complexity. In this study, we developed a framework …
and is still a challenging task due to its complexity. In this study, we developed a framework …
Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition
A challenging issue in the field of the automatic recognition of emotion from speech is the
efficient modelling of long temporal contexts. Moreover, when incorporating long-term …
efficient modelling of long temporal contexts. Moreover, when incorporating long-term …
Speech emotion recognition based on convolutional neural network with attention-based bidirectional long short-term memory network and multi-task learning
ZT Liu, MT Han, BH Wu, A Rehman - Applied Acoustics, 2023 - Elsevier
Speech emotion recognition (SER) is a challenging task since the distribution of the features
is different among various people. To improve generalization performance and accuracy of …
is different among various people. To improve generalization performance and accuracy of …