Despite advances in antimicrobial and anti-inflammatory therapies, inflammation and its
consequences still remain a significant problem in medicine. Acute inflammatory responses …

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 …

With the availability of speech data obtained from different devices and varied acquisition
conditions, we are often faced with scenarios, where the intrinsic discrepancy between the …

The performance of speech emotion recognition is affected by the differences in data
distributions between train (source domain) and test (target domain) sets used to build and …

Despite the widespread use of supervised learning methods for speech emotion recognition,
they are severely restricted due to the lack of sufficient amount of labelled speech data for …

We study covariate shift in the context of nonparametric regression. We introduce a new
measure of distribution mismatch between the source and target distributions using the …

In this manuscript, the topic of multi-corpus Speech Emotion Recognition (SER) is
approached from a deep transfer learning perspective. A large corpus of emotional speech …

Automatic speech emotion recognition provides computers with critical context to enable
user understanding. While methods trained and tested within the same dataset have been …

One of the serious obstacles to the applications of speech emotion recognition systems in
real-life settings is the lack of generalization of the emotion classifiers. Many recognition …

In this paper, we propose a novel method for highly efficient exploitation of unlabeled data-
Cooperative Learning. Our approach consists of combining Active Learning and Semi …