Automatic depression assessment based on visual cues is a rapidly growing research
domain. The present exhaustive review of existing approaches as reported in over sixty …

Automatic affect recognition is a challenging task due to the various modalities emotions can
be expressed with. Applications can be found in many domains including multimedia …

To help clinicians to efficiently diagnose the severity of a person's depression, the affective
computing community and the artificial intelligence field have shown a growing interest in …

One's internal state is mainly communicated through nonverbal cues, such as facial
expressions, gestures and tone of voice, which in turn shape the corresponding emotional …

The high prevalence of depression in society has given rise to a need for new digital tools
that can aid its early detection. Among other effects, depression impacts the use of …

The massive and growing burden imposed on modern society by depression has motivated
investigations into early detection through automated, scalable and non-invasive methods …

Predicting emotion intensity and severity of depression are both challenging and important
problems within the broader field of affective computing. As part of the AVEC 2017, we …

Detection of depression from speech has attracted significant research attention in recent
years but remains a challenge, particularly for speech from diverse smartphones in natural …

Bipolar disorder (BD) is a prevalent mental illness which has a negative impact on work and
social function. However, bipolar symptoms are episodic, especially with irregular variations …

Research in the area of automatic monitoring of emotional state from speech permits
envisaging future novel applications for the remote monitoring of some common mental …