Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …

Speech emotion recognition (SER) as a Machine Learning (ML) problem continues to
garner a significant amount of research interest, especially in the affective computing …

Emotional voice conversion (EVC) seeks to convert the emotional state of an utterance while
preserving the linguistic content and speaker identity. In EVC, emotions are usually treated …

Emotional speech synthesis aims to synthesize human voices with various emotional effects.
The current studies are mostly focused on imitating an averaged style belonging to a specific …

Human facial expressions change with different states of health; therefore, a facial-
expression recognition system can be beneficial to a healthcare framework. In this paper, a …

Feedforward neural networks (FFNN) have been utilised for various research in machine
learning and they have gained a significantly wide acceptance. However, it was recently …

Speech signals and glottal signals convey speakers' emotional state along with linguistic
information. To recognize speakers' emotions and respond to it expressively is very much …

Depression is one of the most common mental disorders. Early intervention is very important
for reducing the burden of the disease, but current methods of diagnosis remain limited …

Automatic recognition of emotion is important for facilitating seamless interactivity between a
human being and intelligent robot towards the full realization of a smart society. The …

Abstract Speech Emotion Recognition (SER) is one of the front-line research areas. For a
machine, inferring SER is difficult because emotions are subjective and annotation is …