User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …

Superimposition is a composition technique that has been applied successfully in many
areas of software development. Although superimposition is a general-purpose concept, it …

Hidden Markov models (HMMs) have a long tradition in automatic speech recognition (ASR)
due to their capability of capturing temporal dynamic characteristics of speech. For emotion …

Features greatly influence the results of speech emotion recognition, among which Mel-
frequency Cepstral Coefficients (MFCC) is the most commonly used in speech emotion …

There is growing interest in emotion recognition due to its potential in many applications.
However, a pervasive challenge is the presence of data variability caused by factors such as …

Tele-diagnosis or telephone consultation is more commonly used in current pandemic
COVID-19 situation where social distancing is need of hour. Speech based emotion …

In this paper, a novel multiscale amplitude feature is proposed using multiresolution analysis
(MRA) and the significance of the vocal tract is investigated for emotion classification from …

In this paper, we propose to combine the deep learning of feature representation with
multiple instance learning (MIL) to recognize emotion from speech. The key idea of our …

This work addresses the cross-corpora generalization issue for the low-resourced spoken
language identification (LID) problem. We have conducted the experiments in the context of …

Automatic emotion recognition from speech signals is one of the important research areas.
Most speech emotion recognition methods have been proposed, among which ensemble …