Nowadays emotion recognition from speech (SER) is a demanding research area for
researchers because of its wide real-life applications. There are many challenges for SER …

Speech Emotion Recognition (SER) aims to help the machine to understand human's
subjective emotion from only audio in-formation. However, extracting and utilizing …

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 …

This work explores the use of constant-Q transform based modulation spectral features (CQT-
MSF) for speech emotion recognition (SER). The human perception and analysis of sound …

Speech emotion recognition plays an essential role in human-computer interaction.
However, cross-individual representation learning and individual-agnostic systems are …

Speech emotion recognition is a vital contributor to the next generation of human-computer
interaction (HCI). However, current existing small-scale databases have limited the …

Convolutional neural network (CNN) is found to be effective in learning representation for
speech emotion recognition. CNNs do not explicitly model the associations or relative …

Speech emotion recognition (SER) aims to recognize human emotions through in-depth
analysis of audio signals. However, it remains challenging to encode emotional cues and to …

This paper considers the issue of the search and rescue operation of humans after natural or
man-made disasters. This problem arises after several calamities, such as earthquakes …

This work analyzes the constant-Q filterbank-based time-frequency representations for
speech emotion recognition (SER). Constant-Q filterbank provides non-linear spectro …