Affect detection is an important pattern recognition problem that has inspired researchers
from several areas. The field is in need of a systematic review due to the recent influx of …

More than a decade has passed since research on automatic recognition of emotion from
speech has become a new field of research in line with its 'big brothers' speech and speaker …

Multimodal emotion recognition has gained traction in affective computing research
community to overcome the limitations posed by the processing a single form of data and to …

In this paper we present a multimodal approach for the recognition of eight emotions. Our
approach integrates information from facial expressions, body movement and gestures and …

The work presented in this paper aims at assessing human emotions using peripheral as
well as electroencephalographic (EEG) physiological signals on short-time periods. Three …

In this paper a study on multimodal automatic emotion recognition during a speech-based
interaction is presented. A database was constructed consisting of people pronouncing a …

Signals from peripheral physiology (eg, ECG, EMG, and GSR) in conjunction with machine
learning techniques can be used for the automatic detection of affective states. The affect …

As technology and human-computer interaction advances, there is an increased interest in
affective computing. One of the current challenges in computational speech and text …

We present EmoVoice, a framework for emotional speech corpus and classifier creation and
for offline as well as real-time online speech emotion recognition. The framework is intended …

In this paper we present a multimodal approach for the recognition of eight emotions that
integrates information from facial expressions, body movement and gestures and speech …