Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers
Speech is the most natural way of expressing ourselves as humans. It is only natural then to
extend this communication medium to computer applications. We define speech emotion …
extend this communication medium to computer applications. We define speech emotion …
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 …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Survey of deep representation learning for speech emotion recognition
Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …
handcrafted acoustic features using feature engineering. However, the design of …
Building naturalistic emotionally balanced speech corpus by retrieving emotional speech from existing podcast recordings
The lack of a large, natural emotional database is one of the key barriers to translate results
on speech emotion recognition in controlled conditions into real-life applications. Collecting …
on speech emotion recognition in controlled conditions into real-life applications. Collecting …
[PDF][PDF] Improved End-to-End Speech Emotion Recognition Using Self Attention Mechanism and Multitask Learning.
Accurately recognizing emotion from speech is a necessary yet challenging task due to the
variability in speech and emotion. In this paper, we propose a speech emotion recognition …
variability in speech and emotion. In this paper, we propose a speech emotion recognition …
An early study on intelligent analysis of speech under COVID-19: Severity, sleep quality, fatigue, and anxiety
The COVID-19 outbreak was announced as a global pandemic by the World Health
Organisation in March 2020 and has affected a growing number of people in the past few …
Organisation in March 2020 and has affected a growing number of people in the past few …
Domain adversarial for acoustic emotion recognition
M Abdelwahab, C Busso - IEEE/ACM Transactions on Audio …, 2018 - ieeexplore.ieee.org
The performance of speech emotion recognition is affected by the differences in data
distributions between train (source domain) and test (target domain) sets used to build and …
distributions between train (source domain) and test (target domain) sets used to build and …
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 …
Multi-task semi-supervised adversarial autoencoding for speech emotion recognition
Inspite the emerging importance of Speech Emotion Recognition (SER), the state-of-the-art
accuracy is quite low and needs improvement to make commercial applications of SER …
accuracy is quite low and needs improvement to make commercial applications of SER …