While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

Multimodal human–computer interaction (HCI) systems pledge a more human–human-like
interaction between machines and humans. Their prowess in emanating an unambiguous …

We present the MSP-IMPROV corpus, a multimodal emotional database, where the goal is
to have control over lexical content and emotion while also promoting naturalness in the …

Recently, studies have been performed on harmony features for speech emotion
recognition. It is found in our study that the first-and second-order differences of harmony …

In this project, we aim to classify the speech taken as one of the four emotions namely,
sadness, anger, fear and happiness. The samples that have been taken to complete this …

This study introduces a method to design a curriculum for machine-learning to maximize the
efficiency during the training process of deep neural networks (DNNs) for speech emotion …

The search of a small acoustic feature set for emotion recognition faces three main
challenges. Such a feature set must be robust to large diversity of contexts in real-life …

In this work, we explore the use of speaker conditioning sub-networks for speaker
adaptation in a deep neural network (DNN) based speech emotion recognition (SER) …

Introduction Digital health interventions are an effective way to treat depression, but it is still
largely unclear how patients' individual symptoms evolve dynamically during such …

Humour is one of the most subtle and contextualised behavioural patterns to study in social
psychology and has a major impact on human emotions, social cognition, behaviour, and …