Speech is an effective medium to express emotions and attitude through language. Finding
the emotional content from a speech signal and identify the emotions from the speech …

Speech emotion recognition (SER) systems identify emotions from the human voice in the
areas of smart healthcare, driving a vehicle, call centers, automatic translation systems, and …

As an essential way of human emotional behavior understanding, speech emotion
recognition (SER) has attracted a great deal of attention in human-centered signal …

Feature selection is a crucial step in the development of a system for identifying emotions in
speech. Recently, the interaction between features generated from the same audio source …

Emotion recognition from speech signals is an interesting research with several applications
like smart healthcare, autonomous voice response systems, assessing situational …

Speech emotion recognition is an important aspect of emotional state recognition in human–
machine interaction. Approaches using speech-to-image transforms have become popular …

In this paper, we propose supervised dictionary learning (SDL) by incorporating information
on class labels into the learning of the dictionary. To this end, we propose to learn the …

Recently, a supervised dictionary learning (SDL) approach based on the Hilbert-Schmidt
independence criterion (HSIC) has been proposed that learns the dictionary and the …

We investigate the performance of features that can capture nonlinear recurrence dynamics
embedded in the speech signal for the task of Speech Emotion Recognition (SER) …

Since breath sound (BS) contains important indicators of respiratory health and disease,
analysis and detection of BS has become an important topic, with diagnostic and …