Efficient and reliable social bot classification is crucial for detecting information manipulation
on social media. Despite rapid development, state-of-the-art bot detection models still face …

Paralinguistic analysis is increasingly turning into a mainstream topic in speech and
language processing. This article aims to provide a broad overview of the constantly …

With recent advances in machine-learning techniques for automatic speech analysis (ASA)-
the computerized extraction of information from speech signals-there is a greater need for …

This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …

We present an extensive study on the performance of data agglomeration and decision-level
fusion for robust cross-corpus emotion recognition. We compare joint training with multiple …

Bot Detection is crucial in a world where Online Social Networks (OSNs) play a pivotal role
in our lives as public communication channels. This task becomes highly relevant in crises …

We present a fully automatic multimodal emotion recognition system based on three novel
peak frame selection approaches using the video channel. Selection of peak frames (ie …

This chapter provides an overview over recent developments in naturalistic emotion
recognition based on acoustic and linguistic cues. It discusses a variety of use‐cases where …

We investigate strategies for selection of databases and instances for training cross-corpus
emotion recognition systems, that is, systems that generalize across different labelling …

Using data with high quality annotation is crucial in emotion recognition applications,
especially because the task is subjective and the raters may exhibit disagreement with …