Introduction Automated computational assessment of neuropsychological tests would
enable widespread, cost‐effective screening for dementia. Methods A novel natural …

The prediction of valence from speech is an important, but challenging problem. The
expression of valence in speech has speaker-dependent cues, which contribute to …

The rapid development and ubiquity of mobile and wearable devices promises to enable
researchers to monitor users' granular emotional data in a less intrusive manner …

Objective The purpose of this study was to identify objective measures that predict surgeon
nontechnical skills (NTS) during surgery. Background NTS are cognitive and social skills …

Automatic speech emotion recognition is an important research topic for human-computer
interaction and affective computing. Over ten million people speak the Quechua language …

Successful conversational interaction with a social robot requires not only an assessment of
a user's contribution to an interaction, but also awareness of their emotional and attitudinal …

The Trier Social Stress Test (TSST) protocol is a widely accepted method of inducing social
and/or cognitive stress in participants and studying its effects. Traditionally, this protocol is …

Many features have been proposed for detecting emotions from speech. Their detection
performance is influenced by the change in contextual parameters such as background …

The rapidly growing number of depressed people increases the burden of clinical diagnosis.
Due to the abnormal speech signal of depressed patients, automatic audio-based …

An important task in several wellness applications is detection of emotional valence from
speech. Two types of features of speech signals are used to detect valence: acoustic …