An engineering view on emotions and speech: From analysis and predictive models to responsible human-centered applications
The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …
devices has increased the public and industry focus on speech emotion recognition (SER) …
An octonion-based nonlinear echo state network for speech emotion recognition in Metaverse
F Daneshfar, MB Jamshidi - Neural Networks, 2023 - Elsevier
While the Metaverse is becoming a popular trend and drawing much attention from
academia, society, and businesses, processing cores used in its infrastructures need to be …
academia, society, and businesses, processing cores used in its infrastructures need to be …
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 …
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 …
[PDF][PDF] Improving depression prediction accuracy using fisher score-based feature selection and dynamic ensemble selection approach based on acoustic features of …
N Janardhan, N Kumaresh - Traitement du Signal, 2022 - researchgate.net
Accepted: 13 February 2022 Depression affects over 322 million people, and it is the most
common source of disability worldwide. Literature in speech processing revealed that …
common source of disability worldwide. Literature in speech processing revealed that …
A hybrid echo state network for hypercomplex pattern recognition, classification, and big data analysis
MB Jamshidi, F Daneshfar - 2022 12th International …, 2022 - ieeexplore.ieee.org
Processing big data with high-dimensional forms is one the most challenging parts of
analyzing different signals and systems for various applications, including decision-making …
analyzing different signals and systems for various applications, including decision-making …
Effect on speech emotion classification of a feature selection approach using a convolutional neural network
Speech emotion recognition (SER) is a challenging issue because it is not clear which
features are effective for classification. Emotionally related features are always extracted …
features are effective for classification. Emotionally related features are always extracted …
Emotion detection from multilingual audio using deep analysis
Human emotion detection from multiple languages is a very challenging job. In this work, we
have used language emotional databases of various languages such as–Ryerson-Audio …
have used language emotional databases of various languages such as–Ryerson-Audio …
Fusion-based speech emotion classification using two-stage feature selection
Speech emotion recognition plays an important role in human–computer interaction, which
uses speech signals to determine the emotional state. Previous studies have proposed …
uses speech signals to determine the emotional state. Previous studies have proposed …
Analyzing Inference Privacy Risks Through Gradients In Machine Learning
In distributed learning settings, models are iteratively updated with shared gradients
computed from potentially sensitive user data. While previous work has studied various …
computed from potentially sensitive user data. While previous work has studied various …